Amazon Dynamo DB Connection Details

Introduction

Connector Version

This documentation is based on version 25.0.9368 of the connector.

Get Started

Amazon DynamoDB Version Support

The connector uses the current version of the Amazon DynamoDB REST API, version 2012-08-10, to enable read/write access to DynamoDB instances.

Establish a Connection

Connect to DynamoDB

Specify the following to connect to data:

• Domain: Set this if you want to use a domain name you have associated with AWS.
• AWSRegion: Set this to the region where your Amazon DynamoDB data is hosted.

Authenticate to DynamoDB

Obtain AWS Keys

To obtain the credentials for an IAM user:

1. Sign into the IAM console.
2. In the navigation pane, select Users.
3. To create or manage the access keys for a user, select the user and then navigate to the Security Credentials tab.

To obtain the credentials for your AWS root account:

1. Sign into the AWS Management console with the credentials for your root account.
2. Select your account name or number.
3. In the menu that displays, select My Security Credentials.
4. To manage or create root account access keys, click Continue to Security Credentials and expand the "Access Keys" section.

Root Credentials

To authenticate using account root credentials, set these parameters:

• AuthScheme: AwsRootKeys.
• AWSAccessKey: The access key associated with the AWS root account.
• AWSSecretKey: The secret key associated with the AWS root account.

If multi-factor authentication is required, specify the following:

• CredentialsLocation: The location of the settings file where MFA credentials are saved. See the Credentials File Location page under Connection String Options for more information.
• MFASerialNumber: The serial number of the MFA device if one is being used.
• MFAToken: The temporary token available from your MFA device.

This causes the connector to submit the MFA credentials in the request to retrieve temporary authentication credentials.

Temporary Credentials

To authenticate using temporary credentials, specify the following:

• AuthScheme: TemporaryCredentials.
• AWSAccessKey: The access key of the IAM user who will assume the role.
• AWSSecretKey: The secret key of the IAM user who will assume the role.
• AWSSessionToken: Your AWS session token, provided with your temporary credentials. For details, see AWS Identity and Access Management User Guide.

The connector can now request resources using the same permissions provided by long-term credentials (such as IAM user credentials) for the lifespan of the temporary credentials.

To authenticate using both temporary credentials and an IAM role, set all the parameters described above, and specify these additional parameters:

• AWSRoleARN: The Role ARN for the role you'd like to authenticate with. This prompts the connector to retrieve credentials for the specified role.
• AWSExternalId (optional): Only required if you are assuming a role in another AWS account.

If multi-factor authentication is required, specify the following:

• CredentialsLocation: The location of the settings file where MFA credentials are saved. See the Credentials File Location page under Connection String Options for more information.
• MFASerialNumber: The serial number of the MFA device if one is being used.
• MFAToken: The temporary token available from your MFA device.

This causes the connector to submit the MFA credentials in the request to retrieve temporary authentication credentials.

EC2 Instances

Set AuthScheme to AwsEC2Roles.

If you are using the connector from an EC2 Instance and have an IAM Role assigned to the instance, you can use the IAM Role to authenticate. Since the connector automatically obtains your IAM Role credentials and authenticates with them, it is not necessary to specify AWSAccessKey and AWSSecretKey.

If you are also using an IAM role to authenticate, you must additionally specify the following:

• AWSRoleARN: Specify the Role ARN for the role you'd like to authenticate with. This will cause the connector to attempt to retrieve credentials for

  the specified role.

• AWSExternalId (optional): Only required if you are assuming a role in another AWS account.

IMDSv2 Support

The Amazon DynamoDB connector now supports IMDSv2. Unlike IMDSv1, the new version requires an authentication token. Endpoints and response are the same in both versions.

In IMDSv2, the Amazon DynamoDB connector first attempts to retrieve the IMDSv2 metadata token and then uses it to call AWS metadata endpoints. If it is unable to retrieve the token, the connector reverts to IMDSv1.

AWS Web Identity

Set AuthScheme to AwsWebIdentity.

If you are either using Amazon DynamoDB from a container configured to assume role with web identity (such as a Pod in an EKS cluster with an OpenID Provider) OR have authenticated with a web identity provider associated with an IAM role (and have thus obtained an identity token), you can exchange the web identity token and IAM role information for temporary security credentials to authenticate and access AWS services.

If the container has AWS_ROLE_ARN and AWS_WEB_IDENTITY_TOKEN_FILE specified in the environment variables, Amazon DynamoDB automatically obtains the credentials.

You can also authenticate by specifying both AWSRoleARN and AWSWebIdentityToken to execute the AssumeRoleWithWebIdentity API operation.

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AWS IAM Roles

Set AuthScheme to AwsIAMRoles.

In some circumstances it may be preferable to use an IAM role for authentication, rather than use the direct security credentials of an AWS root user. If you are specifying the AWSAccessKey and AWSSecretKey of an AWS root user, you may not use roles.

To authenticate as an AWS role, set these properties:

• AWSAccessKey: The access key of the IAM user to assume the role for.

• AWSSecretKey: The secret key of the IAM user to assume the role for.

• AWSRoleARN: Specify the Role ARN for the role you'd like to authenticate with. This will cause the connector to attempt to retrieve credentials for

  the specified role.

• AWSExternalId (optional): Only required if you are assuming a role in another AWS account.

If multi-factor authentication is required, specify the following:

• CredentialsLocation: The location of the settings file where MFA credentials are saved. See the Credentials File Location page under Connection String Options for more information.
• MFASerialNumber: The serial number of the MFA device if one is being used.
• MFAToken: The temporary token available from your MFA device.

This causes the connector to submit the MFA credentials in the request to retrieve temporary authentication credentials.

ADFS

To connect to ADFS, set these properties:

• AuthScheme: ADFS.
• User: The authenticating ADFS user.
• Password: The password of the authenticating ADFS user.
• SSOLoginURL: The SSO provider's login URL.

Example connection string:

AuthScheme=ADFS; AWSRegion=Ireland; User=user@cdata.com; Password=CH8WerW121235647iCa6; SSOLoginURL='https://adfs.domain.com'; AWSRoleArn=arn:aws:iam:1234:role/ADFS_SSO; AWSPrincipalArn=arn:aws:iam:1234:saml-provider/ADFSProvider; S3StagingDirectory=s3://athena/staging;

Okta

To connect to Okta, set these properties:

• AuthScheme: Okta.
• User: The authentiating Okta user.
• Password: The password of the authenticating Okta user.
• SSOLoginURL: The SSO provider's login URL.

If you are either using a trusted application or proxy that overrides the Okta client request OR configuring MFA, you must use combinations of SSOProperties to authenticate using Okta. Set any of the following, as applicable:

• APIToken: When authenticating a user via a trusted application or proxy that overrides the Okta client request context, set this to the API Token the customer created from the Okta organization.

• MFAType: If you have configured the MFA flow, set this to one of the following supported types: OktaVerify, Email, or SMS.

• MFAPassCode: If you have configured the MFA flow, set this to a valid passcode.

  If you set this to empty or an invalid value, the connector issues a one-time password challenge to your device or email. After the passcode is received, reopen the connection where the retrieved one-time password value is set to the MFAPassCode connection property.

• MFARememberDevice: True by default. Okta supports remembering devices when MFA is required. If remembering devices is allowed according to the configured authentication policies, the connector sends a device token to extend MFA authentication lifetime. If you do not want MFA to be remembered, set this variable to False.

Example connection string:

AuthScheme=Okta; AWSRegion=Ireland; User=user@cdata.com; Password=CH8WerW121235647iCa6; SSOLoginURL='https://cdata-us.okta.com/home/amazon_aws/0oa35m8arsAL5f5NrE6NdA356/272'; SSOProperties='ApiToken=01230GGG2ceAnm_tPAf4MhiMELXZ0L0N1pAYrO1VR-hGQSf;'; AWSRoleArn=arn:aws:iam:1234:role/Okta_SSO; AWSPrincipalARN=arn:aws:iam:1234:saml-provider/OktaProvider; S3StagingDirectory=s3://athena/staging;

PingFederate

To connect to PingFederate, set these properties:

• AuthScheme: PingFederate.
• User: The authenticating PingFederate user.
• Password: The authenticating user's PingFederate password.
• SSOLoginURL: The SSO provider's login URL.
• AWSRoleARN (optional): If you have multiple role ARNs, specify the one you want to use for authorization.
• AWSPrincipalARN (optional): If you have multiple principal ARNs, specify the one you want to use for authorization.
• SSOExchangeURL: The Partner Service Identifier URI configured in your PingFederate server instance under: SP Connections > SP Connection > WS-Trust > Protocol Settings. This should uniquely identify a PingFederate SP Connection, so it is a good idea to set it to your AWS SSO ACS URL. You can find it under AWS SSO > Settings > View Details next to the Authentication field.
• SSOProperties (optional): If you want to include your username and password as an authorization header in requests to Amazon S3, set this to Authscheme=Basic.

To enable mutual SSL authentication for SSOLoginURL, the WS-Trust STS endpoint, configure these SSOProperties:

• SSLClientCert
• SSLClientCertType
• SSLClientCertSubject
• SSLClientCertPassword

Example connection string:

authScheme=pingfederate;SSOLoginURL=https://mycustomserver.com:9033/idp/sts.wst;SSOExchangeUrl=https://us-east-1.signin.aws.amazon.com/platform/saml/acs/764ef411-xxxxxx;user=admin;password=PassValue;AWSPrincipalARN=arn:aws:iam:215338515180:saml-provider/pingFederate;AWSRoleArn=arn:aws:iam:215338515180:role/SSOTest2;

Credentials Files

You can use any credentials file to authenticate, including any configurations related to AccessKey/SecretKey authentication, temporary credentials, role authentication, or MFA.

To do this, set these properties:

• AuthScheme: AwsCredentialsFile.
• AWSCredentialsFile: The location of your credentials file.
• AWSCredentialsFileProfile (optional): The name of the profile you would like to use from the specified credentials file. If not specified, the default profile is used.

For further information, see AWS Command Line Interface User Guide.

AWS Cognito Credentials

If you want to use the connector with a user registered in a User Pool in AWS Cognito, set these properties:

• AuthScheme: Either AwsCognitoSrp (recommended) or AwsCognitoBasic.
• AWSCognitoRegion: The User Pool region.
• AWSUserPoolId: The User Pool ID.
• AWSUserPoolClientAppId: The User Pool Client App ID.
• AWSUserPoolClientAppSecret: The User Pool Client Secret.
• AWSIdentityPoolId: The Identity Pool ID of the Identity Pool that is linked with the User Pool.
• User: The username of the user registered in the User Pool.
• Password: The password of the user registered in the User Pool.

Fine-Tuning Data Access

Infer the Data Type

You can use the following properties to configure automatic data type detection, which is enabled by default.

• TypeDetectionScheme: You can use this property to enable or disable automatic type detection based on the value specified in RowScanDepth.
• RowScanDepth: This property determines the number of rows that will be scanned to determine column data types.
• IgnoreTypes: The data types that should be ignored and resolve to varchar data types. By default, Date, Time, and Datetime types are ignored. This is because Amazon DynamoDB does not support them as types. Any filtering of these columns may be done only as their original varchar data type.

Fine Tuning Data Access

You can use the following properties to gain greater control over Amazon DynamoDB API features and the strategies the connector uses to surface them:

• GenerateSchemaFiles: This property enables you to persist table metadata in static schema files that are easy to customize, to change column data types, for example. You can set this property to "OnStart" to generate schema files for all tables in your database at connection. Or, you can generate schemas as you execute SELECT queries to tables. The resulting schemas are based on the connection properties you use to configure Automatic Schema Discovery.

• UseSimpleNames: Amazon DynamoDB supports attribute names with special characters that many database-oriented tools do not support.

  In addition, Amazon DynamoDB table names can include dots and dashes -- the connector interprets dots within table names as hierarchy separators that enable you to drill down to nested fields, similar to XPath.

  You can use this property to replace any nonalphanumeric character with an underscore.

• SeparatorCharacter: You can use this property to more easily access nested fields when Querying Documents and Lists; specify the hierarchy separator with this property. By default, this character is the '.' (dot) character.

Performance

Set a Retry Interval

You can set the following properties to retry queries instead of returning a temporary error such as "maximum throughput exceeded":

• [RetryWaitTime](#RSBDynamoDB_p_RetryWaitTime): The minimum number of milliseconds the connector will wait to retry a request.
• [MaximumRequestRetries](#RSBDynamoDB_p_MaximumRequestRetries): The maximum number of times to retry a request.

The Jitterbit Connector for Amazon DynamoDB also has two seperate APIs that may be used depending on the query, PartiQL and Scan. The API that is used depends on the query that is executed.

PartiQL

PartiQL is used on any INSERT/update/delete request query, as well as any select that contains a filter. This is due to the PartiQL API containing more advanced filtering capabilities than the older Scan endpoint. In general, queries where a significant portion of the result is filtered out can be expected to execute faster than a query with very little filtered.

Use Paging Effectively

You can use the Pagesize property to optimize use of your provisioned throughput, based on the size of your items and Amazon DynamoDB's 1MB page size. Set this property to the number of items to return.

Generally, a smaller page size reduces spikes in throughput that cause throttling. A smaller page size also inserts pauses between requests. This interval evens out the distribution of requests and allows more requests to be successful by avoiding throttling.

Scans

A Scan will occur during a SELECT query that contains no filter. In this case, all results must be retrieved, so there is no advantage in using the PartiQL API. Executing a Scan will retrieve all results, but the API contains a key feature that gives it better performance than an unfiltered PartiQL query: multiple threads. The ThreadCount connection property may be set to influence how many threads will be used when executing a Scan request. Using more threads will cause more memory to be taken up, but will result in faster results per thread. The default is 4. This works best on tables where a high or variable throughput is provisioned.

In cases where the maximum throughput for a table would be exceeded on a single thread, there is no benefit to using a Scan over the single threaded PartiQL API. The Amazon DynamoDB will simply throttle all threads until the maximum throughput is no longer exceeded.

Minimum IAM Requirements

We recommend using predefined roles for services rather than creating custom IAM policies. Predefined roles for Amazon DynamoDB are

• AmazonDynamoDBReadOnlyAccess-grants read-only access to DynamoDB resources through the AWS Management Console.
• AmazonDynamoDBFullAccess-grants full access to DynamoDB resources through the AWS Management Console.

If you want to create custom polices, use the roles described in the table below. Note that the specific policies required by the Amazon DynamoDB driver are subject to change in future releases. Amazon DynamoDB requires at a mininum the following permissions:

"Resource": [
"arn:aws:dynamodb:us-east-1:987654321098:table/Customers",
"arn:aws:dynamodb:us-east-1:987654321098:table/Orders"
]

      {
"Effect": "Allow",
"Action": [
"dynamodb:DescribeTable"
],
"Resource": [
"arn:aws:dynamodb:us-east-1:987654321098:table/Customers",
"arn:aws:dynamodb:us-east-1:987654321098:table/Orders"
]
}

"Resource": "arn:aws:dynamodb:us-east-1:987654321098:table/*"

Important Notes

Configuration Files and Their Paths

• All references to adding configuration files and their paths refer to files and locations on the Jitterbit agent where the connector is installed. These paths are to be adjusted as appropriate depending on the agent and the operating system. If multiple agents are used in an agent group, identical files will be required on each agent.

NoSQL Database

Amazon DynamoDB is a schemaless database that provides high performance, availability, and scalability. These features are not necessarily incompatible with a standards-compliant query language like SQL-92. In this section we will show various schemes that the connector offers to bridge the gap with relational SQL and a document database.

The connector models the schemaless Amazon DynamoDB tables into relational tables and translates SQL queries into Amazon DynamoDB queries to get the requested data. The connector offers two ways, Automatic Schema Discovery and Custom Schema Definitions, to model Amazon DynamoDB tables as relational tables.

The Automatic Schema Discovery scheme automatically finds the data types in a Amazon DynamoDB table by scanning a configured number of rows of the table. You can use RowScanDepth, FlattenArrays, and FlattenObjects to control the relational representation of the tables in Amazon DynamoDB.

Optionally, you can use Custom Schema Definitions to project your chosen relational structure on top of a Amazon DynamoDB table. This allows you to define your chosen column names, their data types, and the location of their values in the Amazon DynamoDB table.

Automatic Schema Discovery

The connector automatically infers a relational schema by inspecting a series of Amazon DynamoDB documents in a collection. You can use the RowScanDepth property to define the number of documents the connector will scan to do so. The columns identified during the discovery process depend on the FlattenArrays and FlattenObjects properties.

Flatten Objects

If FlattenObjects is set, all nested objects will be flattened into a series of columns. For example, consider the following document:

{
  id: 12,
  name: "Lohia Manufacturers Inc.",
  address: {street: "Main Street", city: "Chapel Hill", state: "NC"},
  offices: ["Chapel Hill", "London", "New York"],
  annual_revenue: 35,600,000
}

This document will be represented by the following columns:

If FlattenObjects is not set, then the address.street, address.city, and address.state columns will not be broken apart. The address column of type string will instead represent the entire object. Its value would be {street: "Main Street", city: "Chapel Hill", state: "NC"}. See JSON Functions for more details on working with JSON aggregates. You can change the separator character in the column name from a dot by setting SeparatorCharacter.

Flatten Arrays

The FlattenArrays property can be used to flatten array values into columns of their own. This is only recommended for arrays that are expected to be short, for example the coordinates below:

"coord": [ -73.856077, 40.848447 ]

The FlattenArrays property can be set to 2 to represent the array above as follows:

It is best to leave other unbounded arrays as they are and piece out the data for them as needed using JSON Functions.

Vertical Flattening

It is possible to retrieve an array of objects as if it were a separate table. Take the following JSON structure from the restaurants table for example:

{
  "restaurantid" : "30075445",
  "address" : {
    "building" : "1007",
    "coord" : [-73.856077, 40.848447],
    "street" : "Morris Park Ave",
    "zipcode" : "10462"
  },
  "borough" : "Bronx",
  "cuisine" : "Bakery",
  "grades" : [{
      "date" : 1393804800000,
      "grade" : "B",
      "score" : 2
    }, {
      "date" : 1378857600000,
      "grade" : "A",
      "score" : 6
    }, {
      "date" : 1358985600000,
      "grade" : "A",
      "score" : 10
    }],
  "name" : "Morris Park Bake Shop"
}

Vertical flattening will allow you to retrieve the grades array as a separate table by using the syntax below:

SELECT * FROM [restaurants.grades]

This query returns the following data set:

The grades array could also be nested some levels deeper. In that case, the same syntax should be used:

SELECT * FROM [restaurants.cuisine.bakery.grades]

There are also cases where the nested structure includes another array in a higher level. Take the following JSON as an example:

{
  "restaurantid" : "30075445",
  "reviews": [
   {
    "grades": [
     {
      "date": 1393804800000,
      "score": 2,
      "grade": "B"
     },
     {
      "date": 1378857600000,
      "score": 6,
      "grade": "A"
     },
     {
      "date": 1358985600000,
      "score": 10,
      "grade": "A"
     }]
    }],
  "name" : "Morris Park Bake Shop"
}

For this structure, the index of the reviews array will need to get wrapped in square brackets. If they are already being used as escape characters in the SQL query, the square brackets will need to be escaped themselves as shown in the query below:

SELECT * FROM [restaurants.reviews.\[0\].grades]

This query will return the same data set as the JSON structure at the top. Note that this syntax is case sensitive, so make sure to write the field names the same way that they're saved in DynamoDB.

JSON Functions

The connector can return JSON structures as column values. The connector enables you to use standard SQL functions to work with these JSON structures. The examples in this section use the following array:

[
     { "grade": "A", "score": 2 },
     { "grade": "A", "score": 6 },
     { "grade": "A", "score": 10 },
     { "grade": "A", "score": 9 },
     { "grade": "B", "score": 14 }
]

JSON_EXTRACT

The JSON_EXTRACT function can extract individual values from a JSON object. The following query returns the values shown below based on the JSON path passed as the second argument to the function:

SELECT Name, JSON_EXTRACT(grades,'[0].grade') AS Grade, JSON_EXTRACT(grades,'[0].score') AS Score FROM Students;

JSON_COUNT

The JSON_COUNT function returns the number of elements in a JSON array within a JSON object. The following query returns the number of elements specified by the JSON path passed as the second argument to the function:

SELECT Name, JSON_COUNT(grades,'[x]') AS NumberOfGrades FROM Students;

JSON_SUM

The JSON_SUM function returns the sum of the numeric values of a JSON array within a JSON object. The following query returns the total of the values specified by the JSON path passed as the second argument to the function:

SELECT Name, JSON_SUM(score,'[x].score') AS TotalScore FROM Students;

JSON_MIN

The JSON_MIN function returns the lowest numeric value of a JSON array within a JSON object. The following query returns the minimum value specified by the JSON path passed as the second argument to the function:

SELECT Name, JSON_MIN(score,'[x].score') AS LowestScore FROM Students;

JSON_MAX

The JSON_MAX function returns the highest numeric value of a JSON array within a JSON object. The following query returns the maximum value specified by the JSON path passed as the second argument to the function:

SELECT Name, JSON_MAX(score,'[x].score') AS HighestScore FROM Students;

DOCUMENT

The DOCUMENT function can be used to retrieve the entire document as a JSON string. See the following query and its result as an example:

SELECT DOCUMENT(*) FROM Customers;

The query above will return the entire document as shown.

{ "id": 12, "name": "Lohia Manufacturers Inc.", "address": { "street": "Main Street", "city": "Chapel Hill", "state": "NC"}, "offices": [ "Chapel Hill", "London", "New York" ], "annual_revenue": 35,600,000 }

DynamoDB Queries

Because Amazon DynamoDB is a NoSQL data source, queries need to be handled a bit differently than standard relational databases.

Value-Sensitive Queries

The lack of a required data type for a given column means that you could store different types of data in a single column. For instance, one row could have a String called EmailAddresses and another could have a StringSet also called EmailAddresses. For these and other kinds of cases, the connector largely determines what data type to use based on the values in the query.

For instance, say you have an Items table where the PartNumber could store either a String or a Number. To get back a part with the PartNumber of the number value 12345, you would issue the following query:

SELECT Name, Location, Quantity, PartNumber FROM Items WHERE PartNumber = 12345

Alternatively, the PartNumber could have been stored as the string "12345". To get back a part with the PartNumber of the literal string 12345, issue the following query:

SELECT Name, Location, Quantity, PartNumber FROM Items WHERE PartNumber = '12345'

If the data type of the specified value is not ambiguous, it is always used before the autodetected data type. In both of these cases if a parameter was used instead of of a hardcoded value, then the data type of the parameter would be used to determine what type to submit to Amazon DynamoDB.

Detected Column Data Type

If a value is not obvious based purely on the detected data type, the connector compares it to the autodetected column. For instance, if you want to insert a column called Coordinates into the Location table, your INSERT would look like:

INSERT INTO Locations (Address, Coordinates) VALUES ('123 Fake Street', '[40.7127, 74.0059]')

Based on the input value alone, the detected data type is a string. However, because a Coordinates column was previously autodetected, the connector inserts a NumberSet and not a simple String.

If a Coordinates column was not autodetected when scanning the Locations table, the data type of the inserted value is used.

In this case, we could still resolve that the INSERT is a NumberSet, but it will cost a bit more overhead to do this.

Count

Amazon DynamoDB supports 2 different methods of of using the COUNT aggregate function. To simply return the number of Items in you table, issue the following query:

SELECT COUNT(*) FROM MyTable

The Jitterbit Connector for Amazon DynamoDB will read the ItemCount from the DescribeTable Action. This avoids using too many read units to scan the full table. However, DynamoDB updates this value approximately every six hours and recent changes might not be reflected in this value.

Issuing the below example queries will instead scan the full table for count:

SELECT COUNT(*) FROM MyTable WHERE MyInt > 10
SELECT COUNT(MyInt) FROM MyTable

Query Documents and Lists

Amazon DynamoDB documents and lists are supported with the Jitterbit Connector for Amazon DynamoDB. You can access documents and lists directly at the root level or use the '.' character as a hierarchy divider to drill down to documents and lists.

Report Values in Documents and Lists

When data types are autodetected, they are reported down to the lowest level that can be reliably detected. For instance, a document called Customer with a child called Address and a child on Address called Street would be represented by the column Customer.Address.Street.

However, this process does not apply to Lists since a list could have any number of entries. Once a List or a Set is detected, additional values are not reported as being available in the table schema.

Get Back Unreported Values

If there are attributes that frequently do not have a value and thus are not autodetected, these can still be retrieved by specifying the correct path to them. For instance, to get the Special attribute from the Customer document:

SELECT [Customer.Address.Street], [Customer.Special] FROM MyTable

Once a List has been detected, additional values are not reported. But individual values on the list can be referenced by specifying '.' and a number. For instance:

SELECT [MyList.0], [MyList.1.Email], [MyList.1.Age] FROM MyTable

This will retrieve the first value on the list and the second value's Email and Age attributes.

Insert Documents and Lists

INSERTs in Amazon DynamoDB require that the full object is specified. Insert a document or list at the root. Pass in the full JSON aggregate. For instance:

INSERT INTO MyTable (PrimaryKey, EmailAddresses, Address, MyList) VALUES ('uniquekey', '["user@email.com", "user2@email2.com"]', '{"Street":"123 Fake Street", "City":"Chapel Hill", "Zip":"27713"}', '[{"S":"somestr"},{"NS":[1,2]},{"N":4}]')

In this case, the EmailAddress is inserted as a StringSet, Address is inserted as a document, and MyList is inserted as a list.

Update Documents and Lists

Updates are supported using the same syntax that is available during selects. Documents and Lists can be specified using the '.' character to specify hierarchy. For instance:

UPDATE MyTable SET [EmailAddress.0]='user@email.com', [EmailAddress.1]='user2@email2.com', [Address.Street]='123 Fake Street', [Address.City]='Chapel Hill', [Address.Zip]='27713', [MyList.0]='somestr', [MyList.1]='[1,2]', [MyList.2]=4 WHERE PrimaryKey='uniquekey'

Note that EmailAddress and MyList must be autodetected to resolve how to handle EmailAddress differently from MyList. If you are in doubt about whether or not something will be automatically detected, specifying the full JSON to update will always work.

Data Type Mapping

Data Type Mappings

The connector maps types from the data source to the corresponding data type available in the schema. Additionally, we will attemp to scan the available data coming back based on the IgnoreTypes connection property. The table below documents these mappings.

Note that depending on the settings of IgnoreTypes, some of these types may not be detected by default. Date, datetime, and time for example are ignored by default as they cannot be filtered server side, and may be inserted / updated in a different format than your existing entries if enabled. Please use caution when enabling them.

FlattenArrays and FlattenObjects may also be used to to flatten the StringSets, NumberSets,

BinarySets, Maps, and Lists into indivudal columns.

Custom Schema Definitions

In addition to Automatic Schema Discovery the connector also allows you to statically define the schema for your Amazon DynamoDB table. Let's consider a schema for the restaurants data set.

Below is an example item from the table:

{
   "address":{
      "building":"461",
      "coord":[
         -74.138492,
         40.631136
      ],
      "street":"Port Richmond Ave",
      "zipcode":"10302"
   },
   "borough":"Staten Island",
   "cuisine":"Other",
   "grades":[

   ],
   "name":"Indian Oven",
   "restaurant_id":"50018994"
}

Define a Custom Schema

You can define a custom schema to extract out nested properties as their own columns. Set the Location property to the file directory that will contain the schema file.

The following schema uses the other:path property to define where the data for a particular column should be retrieved from. Using this model you can flatten arbitrary levels of hierarchy.

The 'other:tableapiname' attribute specifies the table to parse. This attribute gives you the flexibility to use multiple schemas for the same table.

In Custom Schema Example, you will find the complete schema that contains the example above.

<api:info title="StaticRestaurants" other:catalog="" other:schema="AmazonDynamoDB" description="StaticRestaurants" other:tableapiname="StaticRestaurants"  other:version="20">
  <attr   name="id"      xs:type="decimal"   key="true"   columnsize="17"     precision="38"   scale="6"   readonly="false"   description="Dynamic Column."   other:dynamodatatype="N"   other:relativepath="restaurant_id"   other:filterable="true"   other:fullpath="restaurant_id"      other:apiname="&amp;quot;restaurant_id&amp;quot;"                          />
  <attr   name="borough"            xs:type="string"                 columnsize="2000"                                readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="borough"         other:filterable="true"   other:fullpath="borough"            other:apiname="&amp;quot;borough&amp;quot;"                                />
  <attr   name="address_zipcode"    xs:type="int"                    columnsize="4"      precision="10"               readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="zipcode"         other:filterable="true"   other:fullpath="address.zipcode"    other:apiname="&amp;quot;address&amp;quot;.&amp;quot;zipcode&amp;quot;"    />
  <attr   name="address_coord_0"    xs:type="double"                 columnsize="8"      precision="15"               readonly="false"   description="Dynamic Column."   other:dynamodatatype="N"   other:relativepath="coord"           other:filterable="true"   other:fullpath="address.coord[0]"   other:apiname="&amp;quot;address&amp;quot;.&amp;quot;coord&amp;quot;[0]"   />
  <attr   name="address_coord_1"    xs:type="double"                 columnsize="8"      precision="15"               readonly="false"   description="Dynamic Column."   other:dynamodatatype="N"   other:relativepath="coord[1]"        other:filterable="true"   other:fullpath="address.coord[1]"   other:apiname="&amp;quot;address&amp;quot;.&amp;quot;coord&amp;quot;[1]"   />
  <attr   name="address_building"   xs:type="int"                    columnsize="4"      precision="10"               readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="building"        other:filterable="true"   other:fullpath="address.building"   other:apiname="&amp;quot;address&amp;quot;.&amp;quot;building&amp;quot;"   />
  <attr   name="address_street"     xs:type="string"                 columnsize="2000"                                readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="street"          other:filterable="true"   other:fullpath="address.street"     other:apiname="&amp;quot;address&amp;quot;.&amp;quot;street&amp;quot;"     />
  <attr   name="name"               xs:type="string"                 columnsize="2000"                                readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="name"            other:filterable="true"   other:fullpath="name"               other:apiname="&amp;quot;name&amp;quot;"                                   />
  <attr   name="cuisine"            xs:type="string"                 columnsize="2000"                                readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="cuisine"         other:filterable="true"   other:fullpath="cuisine"            other:apiname="&amp;quot;cuisine&amp;quot;"                                />
</api:info>

Custom Schema Example

This section contains a complete schema. The info section enables a relational view of a Amazon DynamoDB table. For more details, see Custom Schema Definitions. The table below allows the SELECT, INSERT, UPDATE, and DELETE commands as implemented in the GET, POST, MERGE, and DELETE sections of the schema below. Set the Location property to the file directory that will contain the schema file.

Use the 'other:tableapiname' attribute to specify the name of the Amazon DynamoDB table you want to parse. You can use the 'other:tableapiname' attribute to define multiple schemas for the same table. Note: Amazon DynamoDB is case sensitive. Your table name and specified paths must match the case of how your fields appear in Amazon DynamoDB.

The operations, such as dynamodbadoProviderOperationCaller, are internal implementations and can also be copied as is.

<api:script xmlns:api="http://apiscript.com/ns?v1" xmlns:xs="http://www.cdata.com/ns/rsbscript/2" xmlns:other="http://apiscript.com/ns?v1">
  <api:info title="StaticRestaurants" other:catalog="" other:schema="AmazonDynamoDB" description="StaticRestaurants" other:tableapiname="StaticRestaurants"  other:version="20">
    <attr   name="id"      xs:type="decimal"   key="true"   columnsize="17"     precision="38"   scale="6"   readonly="false"   description="Dynamic Column."   other:dynamodatatype="N"   other:relativepath="restaurant_id"   other:filterable="true"   other:fullpath="restaurant_id"      other:apiname="&amp;quot;restaurant_id&amp;quot;"                          />
    <attr   name="borough"            xs:type="string"                 columnsize="2000"                                readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="borough"         other:filterable="true"   other:fullpath="borough"            other:apiname="&amp;quot;borough&amp;quot;"                                />
    <attr   name="address_zipcode"    xs:type="int"                    columnsize="4"      precision="10"               readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="zipcode"         other:filterable="true"   other:fullpath="address.zipcode"    other:apiname="&amp;quot;address&amp;quot;.&amp;quot;zipcode&amp;quot;"    />
    <attr   name="address_coord_0"    xs:type="double"                 columnsize="8"      precision="15"               readonly="false"   description="Dynamic Column."   other:dynamodatatype="N"   other:relativepath="coord"           other:filterable="true"   other:fullpath="address.coord[0]"   other:apiname="&amp;quot;address&amp;quot;.&amp;quot;coord&amp;quot;[0]"   />
    <attr   name="address_coord_1"    xs:type="double"                 columnsize="8"      precision="15"               readonly="false"   description="Dynamic Column."   other:dynamodatatype="N"   other:relativepath="coord[1]"        other:filterable="true"   other:fullpath="address.coord[1]"   other:apiname="&amp;quot;address&amp;quot;.&amp;quot;coord&amp;quot;[1]"   />
    <attr   name="address_building"   xs:type="int"                    columnsize="4"      precision="10"               readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="building"        other:filterable="true"   other:fullpath="address.building"   other:apiname="&amp;quot;address&amp;quot;.&amp;quot;building&amp;quot;"   />
    <attr   name="address_street"     xs:type="string"                 columnsize="2000"                                readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="street"          other:filterable="true"   other:fullpath="address.street"     other:apiname="&amp;quot;address&amp;quot;.&amp;quot;street&amp;quot;"     />
    <attr   name="name"               xs:type="string"                 columnsize="2000"                                readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="name"            other:filterable="true"   other:fullpath="name"               other:apiname="&amp;quot;name&amp;quot;"                                   />
    <attr   name="cuisine"            xs:type="string"                 columnsize="2000"                                readonly="false"   description="Dynamic Column."   other:dynamodatatype="S"   other:relativepath="cuisine"         other:filterable="true"   other:fullpath="cuisine"            other:apiname="&amp;quot;cuisine&amp;quot;"                                />
  </api:info>


  <api:script method="GET">
    <api:call op="dynamodbadoProviderOperationCaller">
      <api:push/>
    </api:call>
  </api:script>

  <api:script method="POST">
    <api:call op="dynamodbadoProviderOperationCaller">
      <api:push/>
    </api:call>
  </api:script>

  <api:script method="MERGE">
    <api:call op="dynamodbadoProviderOperationCaller">
      <api:push/>
    </api:call>
  </api:script>

  <api:script method="DELETE">
    <api:call op="dynamodbadoProviderOperationCaller">
      <api:push/>
    </api:call>
  </api:script>
</api:script>

Advanced Features

This section details a selection of advanced features of the Amazon DynamoDB connector.

Automatic Index Detection

The AutoDetectIndex property provides fast access to items in a table by detecting an alternate index which can be queried in place of the table itself. This secondary index is a data structure that contains a subset of attributes from a table and an alternate key. The benefit of querying an index instead of the main table is skipping a full scan of the main table. This makes the operation much faster.

User Defined Views

The connector supports the use of user defined views, virtual tables whose contents are decided by a pre-configured user defined query. These views are useful when you cannot directly control queries being issued to the drivers. For an overview of creating and configuring custom views, see User Defined Views.

SSL Configuration

Use SSL Configuration to adjust how connector handles TLS/SSL certificate negotiations. You can choose from various certificate formats. For further information, see the SSLServerCert property under "Connection String Options".

Proxy

To configure the connector using private agent proxy settings, select the Use Proxy Settings checkbox on the connection configuration screen.

Query Processing

The connector offloads as much of the SELECT statement processing as possible to Amazon DynamoDB and then processes the rest of the query in memory (client-side).

For further information, see Query Processing.

Log

For an overview of configuration settings that can be used to refine logging, see Logging. Only two connection properties are required for basic logging, but there are numerous features that support more refined logging, which enables you to use the LogModules connection property to specify subsets of information to be logged.

User Defined Views

The Jitterbit Connector for Amazon DynamoDB supports the use of user defined views: user-defined virtual tables whose contents are decided by a preconfigured query. User defined views are useful in situations where you cannot directly control the query being issued to the driver; for example, when using the driver from Jitterbit.

Use a user defined view to define predicates that are always applied. If you specify additional predicates in the query to the view, they are combined with the query already defined as part of the view.

There are two ways to create user defined views:

• Create a JSON-formatted configuration file defining the views you want.
• DDL statements.

Define Views Using a Configuration File

User defined views are defined in a JSON-formatted configuration file called UserDefinedViews.json. The connector automatically detects the views specified in this file.

You can also have multiple view definitions and control them using the UserDefinedViews connection property. When you use this property, only the specified views are seen by the connector.

This user defined view configuration file is formatted so that each root element defines the name of a view, and includes a child element, called query, which contains the custom SQL query for the view.

For example:

{
    "MyView": {
        "query": "SELECT * FROM Account WHERE MyColumn = 'value'"
    },
    "MyView2": {
        "query": "SELECT * FROM MyTable WHERE Id IN (1,2,3)"
    }
}

Use the UserDefinedViews connection property to specify the location of your JSON configuration file. For example:

"UserDefinedViews", "C:\Users\yourusername\Desktop\tmp\UserDefinedViews.json"

Define Views Using DDL Statements

The connector is also capable of creating and altering the schema via DDL Statements such as CREATE LOCAL VIEW, ALTER LOCAL VIEW, and DROP LOCAL VIEW.

Create a View

To create a new view using DDL statements, provide the view name and query as follows:

CREATE LOCAL VIEW [MyViewName] AS SELECT * FROM Customers LIMIT 20;

If no JSON file exists, the above code creates one. The view is then created in the JSON configuration file and is now discoverable. The JSON file location is specified by the UserDefinedViews connection property.

Alter a View

To alter an existing view, provide the name of an existing view alongside the new query you would like to use instead:

ALTER LOCAL VIEW [MyViewName] AS SELECT * FROM Customers WHERE TimeModified > '3/1/2020';

The view is then updated in the JSON configuration file.

Drop a View

To drop an existing view, provide the name of an existing schema alongside the new query you would like to use instead.

DROP LOCAL VIEW [MyViewName]

This removes the view from the JSON configuration file. It can no longer be queried.

Schema for User Defined Views

In order to avoid a view's name clashing with an actual entity in the data model, user defined views are exposed in the UserViews schema by default. To change the name of the schema used for UserViews, reset the UserViewsSchemaName property.

Work with User Defined Views

For example, a SQL statement with a user defined view called UserViews.RCustomers only lists customers in Raleigh:

SELECT * FROM Customers WHERE City = 'Raleigh';

An example of a query to the driver:

SELECT * FROM UserViews.RCustomers WHERE Status = 'Active';

Resulting in the effective query to the source:

SELECT * FROM Customers WHERE City = 'Raleigh' AND Status = 'Active';

That is a very simple example of a query to a user defined view that is effectively a combination of the view query and the view definition. It is possible to compose these queries in much more complex patterns. All SQL operations are allowed in both queries and are combined when appropriate.

SSL Configuration

Customize the SSL Configuration

By default, the connector attempts to negotiate TLS with the server. The server certificate is validated against the default system trusted certificate store. You can override how the certificate gets validated using the SSLServerCert connection property.

To specify another certificate, see the SSLServerCert connection property.

Data Model

Amazon DynamoDB is a highly scalable NoSQL cloud database that works differently than a regular database. The Jitterbit Connector for Amazon DynamoDB enables you to access Amazon DynamoDB data using a standard database-like interface. The following topics describe how we model schemaless Amazon DynamoDB tables as regular Tables and Stored Procedures.

Tables

The list of Tables is dynamically retrieved from your Amazon DynamoDB account. You can use the CreateTable stored procedure to create a table, or you can create tables using the Amazon Web Services Admin Console.

The connector can dynamically detect table schemas at connection time. See Automatic Schema Discovery for more information. This method is useful if the structure of your data is volatile.

You can also save schemas in fixed schema files. The connector's schema files have a simple format. See Custom Schema Definitions for more information on defining and extending static schemas.

Stored Procedures

Stored Procedures are actions that are invoked via SQL queries. They perform tasks beyond standard CRUD operations, including creating schemas and tables.

Tables

The list of tables is dynamically retrieved from your Amazon DynamoDB account. You can use the stored procedure to create a new table, or you can create a table using the Amazon Web Services Admin Console.

Because DynamoDB tables are partitioned based on their key, you should take care in selecting a proper key based on the query requirements of your table. Refer to the documentation for DynamoDB for more information about using best practices to model data in DynamoDB tables. DynamoDB supports two types of primary keys:

• Hash Primary Key: This is a single-column key.
• Hash and Range Primary Key: This is a two-column key that includes a hash column and a range column.

The connector will model all key attributes in DynamoDB as key columns.

Table Columns

Since Amazon DynamoDB tables are schemaless, the connector offers the following two mechanisms to uncover the schema.

Dynamic Schemas

The columns of a table are dynamically determined by scanning data in the first few rows. You can adjust the number of rows that are used by modifying the RowScanDepth property. In addition to the name of the column, the row scan also determines the data type. The following table shows how the different data types supported by Amazon DynamoDB are modeled in the connector.

Static Schemas

Instead of using dynamically discovered schemas, you can define your own schemas. This will give you more control over the projected columns and also enable you to use other data types such as boolean, datetime, etc. Refer to the CreateSchema Stored Procedure in order to create your own schema. You can simply specify the FileName (fullpath) and TableName of the new schema file, which should match with the name of the Amazon DynamoDB table, and edit the column listing to use it for your own table.

Schemaless Operations

While the schema of the table is necessary to report metadata, data may be selected, inserted, updated, or deleted from columns that do not exist in the schema. Columns that do not already exist in the table schema will have their data types dynamically determined based on the data that is specified. See DynamoDB Queries for more information.

Stored Procedures

Stored procedures are function-like interfaces that extend the functionality of the connector beyond simple SELECT/INSERT/UPDATE/DELETE operations with Amazon DynamoDB.

Stored procedures accept a list of parameters, perform their intended function, and then return any relevant response data from Amazon DynamoDB, along with an indication of whether the procedure succeeded or failed.

Jitterbit Connector for Amazon DynamoDB Stored Procedures

CreateSchema

Generates a schema file for a specified table or view, detailing its structure and attributes for use in DynamoDB operations.

CreateSchema

Creates a local schema file (.rsd) from an existing table or view in the data model.

The schema file is created in the directory set in the Location connection property when this procedure is executed. You can edit the file to include or exclude columns, rename columns, or adjust column datatypes.

The connector checks the Location to determine if the names of any .rsd files match a table or view in the data model. If there is a duplicate, the schema file will take precedence over the default instance of this table in the data model. If a schema file is present in Location that does not match an existing table or view, a new table or view entry is added to the data model of the connector.

Input

Result Set Columns

CreateTable

Creates a new table in DynamoDB with specified partition and sort keys, along with optional billing mode and capacity settings.

Input

Result Set Columns

System Tables

You can query the system tables described in this section to access schema information, information on data source functionality, and batch operation statistics.

Schema Tables

The following tables return database metadata for Amazon DynamoDB:

• sys_catalogs: Lists the available databases.
• sys_schemas: Lists the available schemas.
• sys_tables: Lists the available tables and views.
• sys_tablecolumns: Describes the columns of the available tables and views.
• sys_procedures: Describes the available stored procedures.
• sys_procedureparameters: Describes stored procedure parameters.
• sys_keycolumns: Describes the primary and foreign keys.
• sys_indexes: Describes the available indexes.

Data Source Tables

The following tables return information about how to connect to and query the data source:

• sys_connection_props: Returns information on the available connection properties.
• sys_sqlinfo: Describes the SELECT queries that the connector can offload to the data source.

Query Information Tables

The following table returns query statistics for data modification queries, including batch operations:

• sys_identity: Returns information about batch operations or single updates.

sys_catalogs

Lists the available databases.

The following query retrieves all databases determined by the connection string:

SELECT * FROM sys_catalogs

Columns

sys_schemas

Lists the available schemas.

The following query retrieves all available schemas:

SELECT * FROM sys_schemas

Columns

sys_tables

Lists the available tables.

The following query retrieves the available tables and views:

SELECT * FROM sys_tables

Columns

sys_tablecolumns

Describes the columns of the available tables and views.

The following query returns the columns and data types for the Account table:

SELECT ColumnName, DataTypeName FROM sys_tablecolumns WHERE TableName='Account'

Columns

sys_procedures

Lists the available stored procedures.

The following query retrieves the available stored procedures:

SELECT * FROM sys_procedures

Columns

sys_procedureparameters

Describes stored procedure parameters.

The following query returns information about all of the input parameters for the CreateSchema stored procedure:

SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'CreateSchema' AND Direction = 1 OR Direction = 2

To include result set columns in addition to the parameters, set the IncludeResultColumns pseudo column to True:

SELECT * FROM sys_procedureparameters WHERE ProcedureName = 'CreateSchema' AND IncludeResultColumns='True'

Columns

Pseudo-Columns

sys_keycolumns

Describes the primary and foreign keys.

The following query retrieves the primary key for the Account table:

SELECT * FROM sys_keycolumns WHERE IsKey='True' AND TableName='Account'

Columns

sys_foreignkeys

Describes the foreign keys.

The following query retrieves all foreign keys which refer to other tables:

SELECT * FROM sys_foreignkeys WHERE ForeignKeyType = 'FOREIGNKEY_TYPE_IMPORT'

Columns

sys_primarykeys

Describes the primary keys.

The following query retrieves the primary keys from all tables and views:

SELECT * FROM sys_primarykeys

Columns

sys_indexes

Describes the available indexes. By filtering on indexes, you can write more selective queries with faster query response times.

The following query retrieves all indexes that are not primary keys:

SELECT * FROM sys_indexes WHERE IsPrimary='false'

Columns

sys_connection_props

Returns information on the available connection properties and those set in the connection string.

The following query retrieves all connection properties that have been set in the connection string or set through a default value:

SELECT * FROM sys_connection_props WHERE Value <> ''

Columns

sys_sqlinfo

Describes the SELECT query processing that the connector can offload to the data source.

Discovering the Data Source's SELECT Capabilities

Below is an example data set of SQL capabilities. Some aspects of SELECT functionality are returned in a comma-separated list if supported; otherwise, the column contains NO.

The following query retrieves the operators that can be used in the WHERE clause:

SELECT * FROM sys_sqlinfo WHERE Name = 'SUPPORTED_OPERATORS'

Note that individual tables may have different limitations or requirements on the WHERE clause; refer to the NoSQL Database section for more information.

Columns

sys_identity

Returns information about attempted modifications.

The following query retrieves the Ids of the modified rows in a batch operation:

SELECT * FROM sys_identity

Columns

sys_information

Describes the available system information.

The following query retrieves all columns:

SELECT * FROM sys_information

Columns

Advanced Configurations Properties

The advanced configurations properties are the various options that can be used to establish a connection. This section provides a complete list of the options you can configure. Click the links for further details.

Connection

AWS Authentication

SSO

SSL

Schema

Miscellaneous

Connection

This section provides a complete list of connection properties you can configure.

UseLakeFormation

When this property is set to true, AWSLakeFormation service will be used to retrieve temporary credentials, which enforce access policies against the user based on the configured IAM role. The service can be used when authenticating through OKTA, ADFS, Microsoft Entra ID, PingFederate, while providing a SAML assertion.

Data Type

bool

Default Value

false

Remarks

When this property is set to true, AWSLakeFormation service will be used to retrieve temporary credentials, which enforce access policies against the user based on the configured IAM role. The service can be used when authenticating through OKTA, ADFS, Microsoft Entra ID, PingFederate, while providing a SAML assertion.

AWS Authentication

This section provides a complete list of AWS authentication properties you can configure.

AuthScheme

Specifies the type of authentication to use when connecting to Amazon DynamoDB. If this property is left blank, the default authentication is used.

Possible Values

ADFS, AwsRootKeys, AwsIAMRoles, AwsEC2Roles, AwsWebIdentity, AwsCredentialsFile, Okta, Keycloak, TemporaryCredentials, PingFederate, AwsCognitoBasic, AwsCognitoSrp

Data Type

string

Default Value

AwsRootKeys

Remarks

• TemporaryCredentials: Authenticate using temporary security credentials alongside a session token.
• AwsRootKeys: Authenticate using the root user access key and secret, to test something quickly. (Production use cases are encouraged to use something with narrowed permissions.)
• AwsIAMRoles: Authenticate using IAM Roles.
• AwsEC2Roles: Automatically use IAM Roles assigned to the EC2 machine where connector is currently running.
• Okta: Set to use a single sign on connection with OKTA as the identity provider.
• ADFS: Set to use a single sign on connection with ADFS as the identity provider.
• PingFederate: Set to use a single sign on connection with PingFederate as the identity provider.
• AwsCredentialsFile: Set to use a credential file for authentication.
• AwsCognitoSrp: Set to use Cognito based authentication. This is recommended over AwsCognitoBasic because this option does NOT send the password to the server for authentication, instead it uses the SRP protocol.
• AwsCognitoBasic: Set to use Cognito based authentication.

Domain

Specifies your AWS domain name. Use this property to set a custom domain name if your organization has associated one with AWS.

Data Type

string

Default Value

amazonaws.com

Remarks

This property specifies the AWS domain name to use when connecting to services. If your organization uses a custom AWS domain, provide it here. If you do not have a unique domain, use the default value, "amazonaws.com". Ensure the domain name matches your AWS setup to avoid connection errors.

AWSAccessKey

Specifies your AWS account access key. This value is accessible from your AWS security credentials page.

Data Type

string

Default Value

""

Remarks

To find your AWS account access key:

1. Sign into the AWS Management console with the credentials for your root account.
2. Select your account name or number.
3. Select My Security Credentials in the menu.
4. Click Continue to Security Credentials.
5. To view or manage root account access keys, expand the Access Keys section.

AWSSecretKey

Your AWS account secret key. This value is accessible from your AWS security credentials page.

Data Type

string

Default Value

""

Remarks

Your AWS account secret key. This value is accessible from your AWS security credentials page:

1. Sign into the AWS Management console with the credentials for your root account.
2. Select your account name or number and select My Security Credentials in the menu that is displayed.
3. Click Continue to Security Credentials and expand the Access Keys section to manage or create root account access keys.

AWSRoleARN

The Amazon Resource Name of the role to use when authenticating.

Data Type

string

Default Value

""

Remarks

When authenticating outside of AWS, it is common to use a Role for authentication instead of your direct AWS account credentials. Entering the AWSRoleARN will cause the Jitterbit Connector for Amazon DynamoDB to perform a role based authentication instead of using the AWSAccessKey and AWSSecretKey directly. The AWSAccessKey and AWSSecretKey must still be specified to perform this authentication. You cannot use the credentials of an AWS root user when setting RoleARN. The AWSAccessKey and AWSSecretKey must be those of an IAM user.

AWSRegion

The hosting region for your Amazon Web Services.

Possible Values

OHIO, NORTHERNVIRGINIA, NORTHERNCALIFORNIA, OREGON, CAPETOWN, HONGKONG, HYDERABAD, JAKARTA, MALAYSIA, MELBOURNE, MUMBAI, OSAKA, SEOUL, SINGAPORE, SYDNEY, THAILAND, TOKYO, CENTRAL, CALGARY, BEIJING, NINGXIA, FRANKFURT, IRELAND, LONDON, MILAN, PARIS, SPAIN, STOCKHOLM, ZURICH, TELAVIV, MEXICOCENTRAL, BAHRAIN, UAE, SAOPAULO, GOVCLOUDEAST, GOVCLOUDWEST, ISOLATEDUSEAST, ISOLATEDUSEASTB, ISOLATEDUSEASTF, ISOLATEDUSSOUTHF, ISOLATEDUSWEST, ISOLATEDEUWEST

Data Type

string

Default Value

NORTHERNVIRGINIA

Remarks

The hosting region for your Amazon Web Services. Available values are OHIO, NORTHERNVIRGINIA, NORTHERNCALIFORNIA, OREGON, CAPETOWN, HONGKONG, HYDERABAD, JAKARTA, MALAYSIA, MELBOURNE, MUMBAI, OSAKA, SEOUL, SINGAPORE, SYDNEY, THAILAND, TOKYO, CENTRAL, CALGARY, BEIJING, NINGXIA, FRANKFURT, IRELAND, LONDON, MILAN, PARIS, SPAIN, STOCKHOLM, ZURICH, TELAVIV, MEXICOCENTRAL, BAHRAIN, UAE, SAOPAULO, GOVCLOUDEAST, GOVCLOUDWEST, ISOLATEDUSEAST, ISOLATEDUSEASTB, ISOLATEDUSEASTF, ISOLATEDUSSOUTHF, ISOLATEDUSWEST, and ISOLATEDEUWEST.

AWSCredentialsFile

The path to the AWS Credentials File to be used for authentication.

Data Type

string

Default Value

""

Remarks

The path to the AWS Credentials File to be used for authentication. See https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-files.html for more information.

AWSCredentialsFileProfile

The name of the profile to be used from the supplied AWSCredentialsFile.

Data Type

string

Default Value

default

Remarks

The name of the profile to be used from the supplied AWSCredentialsFile. See https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-files.html for more information.

AWSSessionToken

Your AWS session token.

Data Type

string

Default Value

""

Remarks

Your AWS session token. This value can be retrieved in different ways. See this link for more info.

AWSExternalId

A unique identifier that might be required when you assume a role in another account.

Data Type

string

Default Value

""

Remarks

A unique identifier that might be required when you assume a role in another account.

MFASerialNumber

The serial number of the MFA device if one is being used.

Data Type

string

Default Value

""

Remarks

You can find the device for an IAM user by going to the AWS Management Console and viewing the user's security credentials. For virtual devices, this is actually an Amazon Resource Name (such as arn:aws:iam:123456789012:mfa/user).

MFAToken

The temporary token available from your MFA device.

Data Type

string

Default Value

""

Remarks

If MFA is required, this value will be used along with the MFASerialNumber to retrieve temporary credentials to login. The temporary credentials available from AWS will only last up to 1 hour by default (see TemporaryTokenDuration). Once the time is up, the connection must be updated to specify a new MFA token so that new credentials may be obtained.

TemporaryTokenDuration

The amount of time (in seconds) a temporary token will last.

Data Type

string

Default Value

3600

Remarks

Temporary tokens are used with both MFA and Role based authentication. Temporary tokens will eventually time out, at which time a new temporary token must be obtained. For situations where MFA is not used, this is not a big deal. The Jitterbit Connector for Amazon DynamoDB will internally request a new temporary token once the temporary token has expired.

However, for MFA required connection, a new MFAToken must be specified in the connection to retrieve a new temporary token. This is a more intrusive issue since it requires an update to the connection by the user. The maximum and minimum that can be specified will depend largely on the connection being used.

For Role based authentication, the minimum duration is 900 seconds (15 minutes) while the maximum if 3600 (1 hour). Even if MFA is used with role based authentication, 3600 is still the maximum.

For MFA authentication by itself (using an IAM User or root user), the minimum is 900 seconds (15 minutes), the maximum is 129600 (36 hours).

AWSCognitoRegion

The hosting region for AWS Cognito.

Possible Values

OHIO, NORTHERNVIRGINIA, NORTHERNCALIFORNIA, OREGON, CAPETOWN, HONGKONG, HYDERABAD, JAKARTA, MALAYSIA, MELBOURNE, MUMBAI, OSAKA, SEOUL, SINGAPORE, SYDNEY, THAILAND, TOKYO, CENTRAL, CALGARY, BEIJING, NINGXIA, FRANKFURT, IRELAND, LONDON, MILAN, PARIS, SPAIN, STOCKHOLM, ZURICH, TELAVIV, MEXICOCENTRAL, BAHRAIN, UAE, SAOPAULO, GOVCLOUDEAST, GOVCLOUDWEST, ISOLATEDUSEAST, ISOLATEDUSEASTB, ISOLATEDUSEASTF, ISOLATEDUSSOUTHF, ISOLATEDUSWEST, ISOLATEDEUWEST

Data Type

string

Default Value

NORTHERNVIRGINIA

Remarks

The hosting region for AWS Cognito. Available values are OHIO, NORTHERNVIRGINIA, NORTHERNCALIFORNIA, OREGON, CAPETOWN, HONGKONG, HYDERABAD, JAKARTA, MALAYSIA, MELBOURNE, MUMBAI, OSAKA, SEOUL, SINGAPORE, SYDNEY, THAILAND, TOKYO, CENTRAL, CALGARY, BEIJING, NINGXIA, FRANKFURT, IRELAND, LONDON, MILAN, PARIS, SPAIN, STOCKHOLM, ZURICH, TELAVIV, MEXICOCENTRAL, BAHRAIN, UAE, SAOPAULO, GOVCLOUDEAST, GOVCLOUDWEST, ISOLATEDUSEAST, ISOLATEDUSEASTB, ISOLATEDUSEASTF, ISOLATEDUSSOUTHF, ISOLATEDUSWEST, and ISOLATEDEUWEST.

AWSUserPoolId

The User Pool Id.

Data Type

string

Default Value

""

Remarks

You can find this in AWS Cognito -> Manage User Pools -> select your user pool -> General settings -> Pool Id.

AWSUserPoolClientAppId

The User Pool Client App Id.

Data Type

string

Default Value

""

Remarks

You can find this in AWS Cognito -> Manage Identity Pools -> select your user pool -> General settings -> App clients -> App client Id.

AWSUserPoolClientAppSecret

Optional. The User Pool Client App Secret.

Data Type

string

Default Value

""

Remarks

You can find this in AWS Cognito -> Manage Identity Pools -> select your user pool -> General settings -> App clients -> App client secret.

AWSIdentityPoolId

The Identity Pool Id.

Data Type

string

Default Value

""

Remarks

You can find this in AWS Cognito -> Manage Identity Pools -> select your identity pool -> Edit identity pool -> Identity Pool Id

AWSWebIdentityToken

The OAuth 2.0 access token or OpenID Connect ID token that is provided by an identity provider.

Data Type

string

Default Value

""

Remarks

The OAuth 2.0 access token or OpenID Connect ID token that is provided by an identity provider. An application can get this token by authenticating a user with a web identity provider. If not specified, the value for this connection property is automatically obtained from the value of the 'AWS_WEB_IDENTITY_TOKEN_FILE' environment variable.

SSO

This section provides a complete list of SSO properties you can configure.

User

The IDP user used to authenticate the IDP via SSO.

Data Type

string

Default Value

""

Remarks

Together with Password, this field is used to authenticate in SSO connections against the Amazon DynamoDB server.

Password

The password used to authenticate the IDP user via SSO.

Data Type

string

Default Value

""

Remarks

The User and Password are together used in SSO connections to authenticate with the server.

SSOLoginURL

The identity provider's login URL.

Data Type

string

Default Value

""

Remarks

The identity provider's login URL.

SSOProperties

Additional properties required to connect to the identity provider in a semicolon-separated list.

Data Type

string

Default Value

""

Remarks

Additional properties required to connect to the identity provider in a semicolon-separated list. SSOProperties is used in conjunction with the the AWSRoleARN and AWSPrincipalARN. The following section provides an example using the OKTA identity provider.

ADFS

To connect to ADFS, set these properties:

• AuthScheme: ADFS.
• User: The authenticating ADFS user.
• Password: The password of the authenticating ADFS user.
• SSOLoginURL: The SSO provider's login URL.

Example connection string:

AuthScheme=ADFS; AWSRegion=Ireland; User=user@cdata.com; Password=CH8WerW121235647iCa6; SSOLoginURL='https://adfs.domain.com'; AWSRoleArn=arn:aws:iam:1234:role/ADFS_SSO; AWSPrincipalArn=arn:aws:iam:1234:saml-provider/ADFSProvider; S3StagingDirectory=s3://athena/staging;

Okta

To connect to Okta, set these properties:

• AuthScheme: Okta.
• User: The authentiating Okta user.
• Password: The password of the authenticating Okta user.
• SSOLoginURL: The SSO provider's login URL.

If you are either using a trusted application or proxy that overrides the Okta client request OR configuring MFA, you must use combinations of SSOProperties to authenticate using Okta. Set any of the following, as applicable:

• APIToken: When authenticating a user via a trusted application or proxy that overrides the Okta client request context, set this to the API Token the customer created from the Okta organization.

• MFAType: If you have configured the MFA flow, set this to one of the following supported types: OktaVerify, Email, or SMS.

• MFAPassCode: If you have configured the MFA flow, set this to a valid passcode.

  If you set this to empty or an invalid value, the connector issues a one-time password challenge to your device or email. After the passcode is received, reopen the connection where the retrieved one-time password value is set to the MFAPassCode connection property.

• MFARememberDevice: True by default. Okta supports remembering devices when MFA is required. If remembering devices is allowed according to the configured authentication policies, the connector sends a device token to extend MFA authentication lifetime. If you do not want MFA to be remembered, set this variable to False.

Example connection string:

AuthScheme=Okta; AWSRegion=Ireland; User=user@cdata.com; Password=CH8WerW121235647iCa6; SSOLoginURL='https://cdata-us.okta.com/home/amazon_aws/0oa35m8arsAL5f5NrE6NdA356/272'; SSOProperties='ApiToken=01230GGG2ceAnm_tPAf4MhiMELXZ0L0N1pAYrO1VR-hGQSf;'; AWSRoleArn=arn:aws:iam:1234:role/Okta_SSO; AWSPrincipalARN=arn:aws:iam:1234:saml-provider/OktaProvider; S3StagingDirectory=s3://athena/staging;

SSOExchangeURL

The URL used for consuming the SAML response and exchanging it for service specific credentials.

Data Type

string

Default Value

""

Remarks

The Jitterbit Connector for Amazon DynamoDB will use the URL specified here to consume a SAML response and exchange it for service specific credentials. The retrieved credentials are the final piece during the SSO connection that are used to communicate with Amazon DynamoDB.

SSL

This section provides a complete list of SSL properties you can configure.

SSLServerCert

Specifies the certificate to be accepted from the server when connecting using TLS/SSL.

Data Type

string

Default Value

""

Remarks

If using a TLS/SSL connection, this property can be used to specify the TLS/SSL certificate to be accepted from the server. Any other certificate that is not trusted by the machine is rejected.

This property can take the following forms:

If not specified, any certificate trusted by the machine is accepted.

Certificates are validated as trusted by the machine based on the System's trust store. The trust store used is the 'javax.net.ssl.trustStore' value specified for the system. If no value is specified for this property, Java's default trust store is used (for example, JAVA_HOME\lib\security\cacerts).

Use '*' to signify to accept all certificates. Note that this is not recommended due to security concerns.

Schema

This section provides a complete list of schema properties you can configure.

Location

Specifies the location of a directory containing schema files that define tables, views, and stored procedures. Depending on your service's requirements, this may be expressed as either an absolute path or a relative path.

Data Type

string

Default Value

%APPDATA%\AmazonDynamoDB Data Provider\Schema

Remarks

The Location property is only needed if you want to either customize definitions (for example, change a column name, ignore a column, etc.) or extend the data model with new tables, views, or stored procedures.

If left unspecified, the default location is %APPDATA%\AmazonDynamoDB Data Provider\Schema, where %APPDATA% is set to the user's configuration directory:

BrowsableSchemas

Optional setting that restricts the schemas reported to a subset of all available schemas. For example, BrowsableSchemas=SchemaA,SchemaB,SchemaC .

Data Type

string

Default Value

""

Remarks

Listing all available database schemas can take extra time, thus degrading performance. Providing a list of schemas in the connection string saves time and improves performance.

Tables

Optional setting that restricts the tables reported to a subset of all available tables. For example, Tables=TableA,TableB,TableC .

Data Type

string

Default Value

""

Remarks

Listing all available tables from some databases can take extra time, thus degrading performance. Providing a list of tables in the connection string saves time and improves performance.

If there are lots of tables available and you already know which ones you want to work with, you can use this property to restrict your viewing to only those tables. To do this, specify the tables you want in a comma-separated list. Each table should be a valid SQL identifier with any special characters escaped using square brackets, double-quotes or backticks. For example, Tables=TableA,[TableB/WithSlash],WithCatalog.WithSchema.`TableC With Space`.

Views

Optional setting that restricts the views reported to a subset of the available tables. For example, Views=ViewA,ViewB,ViewC .

Data Type

string

Default Value

""

Remarks

Listing all available views from some databases can take extra time, thus degrading performance. Providing a list of views in the connection string saves time and improves performance.

If there are lots of views available and you already know which ones you want to work with, you can use this property to restrict your viewing to only those views. To do this, specify the views you want in a comma-separated list. Each view should be a valid SQL identifier with any special characters escaped using square brackets, double-quotes or backticks. For example, Views=ViewA,[ViewB/WithSlash],WithCatalog.WithSchema.`ViewC With Space`.

Miscellaneous

This section provides a complete list of miscellaneous properties you can configure.

AutoDetectIndex

Specifies whether the provider should automatically detect and use secondary indexes based on the query criteria.

Data Type

bool

Default Value

true

Remarks

This property controls the automatic detection of secondary indexes, which can optimize data selection in DynamoDB tables. By default, this property is set to true, enabling the provider to analyze the query criteria and choose an appropriate secondary index automatically.

• Disabling Automatic Detection: Set this property to false if automatic index selection is not desired, such as when the query logic does not align with the detected index or when you prefer manual control over index usage.
• Manual Index Selection: Use the SecondaryIndexName pseudo-column in your query to specify the index you want to use, bypassing the automatic detection logic.

This property is useful for scenarios where the default behavior does not align with your query optimization strategy, giving you flexibility to fine-tune index usage for your DynamoDB tables.

FlattenArrays

This property flattens nested array elements into individual columns. By default, nested arrays are returned as JSON strings. Set this property to the number of elements to extract from nested arrays.

Data Type

string

Default Value

""

Remarks

Use this property to extract elements from nested arrays and represent them as individual columns. This property is useful for simplifying the representation of short arrays in tabular output. The extracted elements are assigned column names with their zero-based index appended. Any remaining elements in the array are ignored. For example, the following array is flattened into two columns when FlattenArrays is set to 2:

["FLOW-MATIC", "LISP", "COBOL"]

Flattening longer arrays may result in unused elements being discarded, so it is recommended for arrays expected to contain a small number of items.

FlattenObjects

Specifies whether nested object properties are flattened into individual columns.

Data Type

bool

Default Value

true

Remarks

When this property is set to true, object properties are extracted as separate columns. When it is set to false, nested objects within arrays are represented as JSON-formatted strings. Flattening nested objects into individual columns simplifies working with structured data. When enabled, the provider appends the property name to the parent object name to generate column names. This is useful for tabularizing predictable and manageable object structures.

For deeply nested or large JSON objects, consider the performance implications of flattening, as excessive flattening may create an unmanageable number of columns. For objects with unpredictable properties or varying schemas, leaving this property disabled may provide a more flexible representation.

For example, you can flatten the nested objects below at connection time:

[
     { "grade": "A", "score": 2 },
     { "grade": "A", "score": 6 },
     { "grade": "A", "score": 10 },
     { "grade": "A", "score": 9 },
     { "grade": "B", "score": 14 }
]

When FlattenObjects is set to true and FlattenArrays is set to 1, the preceding array is flattened into the following table:

FlexibleSchema

Specifies whether the provider should dynamically scan query result sets for additional metadata. Set to true to enable scanning or false to use a static metadata structure.

Data Type

bool

Default Value

true

Remarks

When enabled, this property allows the provider to dynamically analyze query result sets for additional metadata, ensuring the result schema reflects any changes or variations in the queried data. This property is useful when working with data sources where schema details may vary or are not fully known in advance.

Disabling this property preserves a static metadata structure, which may improve performance when querying data with a consistent schema. Use this property based on the predictability of your data source and performance considerations.

GenerateSchemaFiles

Indicates the user preference as to when schemas should be generated and saved.

Possible Values

Never, OnUse, OnStart, OnCreate

Data Type

string

Default Value

Never

Remarks

This property outputs schemas to .rsd files in the path specified by Location.

Available settings are the following:

• Never: A schema file will never be generated.
• OnUse: A schema file will be generated the first time a table is referenced, provided the schema file for the table does not already exist.
• OnStart: A schema file will be generated at connection time for any tables that do not currently have a schema file.
• OnCreate: A schema file will be generated by when running a CREATE TABLE SQL query.

Note that if you want to regenerate a file, you will first need to delete it.

Generate Schemas with SQL

When you set GenerateSchemaFiles to OnUse, the connector generates schemas as you execute SELECT queries. Schemas are generated for each table referenced in the query.

When you set GenerateSchemaFiles to OnCreate, schemas are only generated when a CREATE TABLE query is executed.

Generate Schemas on Connection

Another way to use this property is to obtain schemas for every table in your database when you connect. To do so, set GenerateSchemaFiles to OnStart and connect.

IgnoreTypes

Specifies which data types should be ignored and reported as strings.

Data Type

string

Default Value

Datetime,Date,Time

Remarks

This property allows you to exclude specific data types from being processed as their native types. When a type is ignored, it is treated as a string. By default, Datetime, Date, and Time are ignored and reported as string values instead of their native types.

This property is useful when compatibility issues or downstream processing requirements necessitate treating certain types as text. For example, applications that do not handle Time data types may benefit from converting them to strings.

MaximumRequestRetries

Specifies the maximum number of times the provider retries a request when a temporary issue is detected. Temporary issues include network interruptions, transient errors, or exceeding operational thresholds.

Data Type

string

Default Value

4

Remarks

This property controls the number of retries the driver attempts when a temporary issue, such as network instability or rate limits, is encountered. For each retry, the connector follows an exponential backoff strategy: the wait time between retries starts at the value specified by RetryWaitTime and doubles with each subsequent retry until the maximum number of retries is reached.

For example, if RetryWaitTime is set to 2 seconds and MaximumRequestRetries is set to 5, the connector waits as follows: 0 seconds (initial attempt), 2 seconds, 4 seconds, 8 seconds, 16 seconds, and 32 seconds.

This property is useful in scenarios where temporary issues are expected, such as high-latency networks or environments with strict API quotas.

MaxRows

Specifies the maximum rows returned for queries without aggregation or GROUP BY.

Data Type

int

Default Value

-1

Remarks

This property sets an upper limit on the number of rows the connector returns for queries that do not include aggregation or GROUP BY clauses. This limit ensures that queries do not return excessively large result sets by default.

When a query includes a LIMIT clause, the value specified in the query takes precedence over the MaxRows setting. If MaxRows is set to "-1", no row limit is enforced unless a LIMIT clause is explicitly included in the query.

This property is useful for optimizing performance and preventing excessive resource consumption when executing queries that could otherwise return very large datasets.

Other

Specifies additional hidden properties for specific use cases. These are not required for typical provider functionality. Use a semicolon-separated list to define multiple properties.

Data Type

string

Default Value

""

Remarks

This property allows advanced users to configure hidden properties for specialized scenarios. These settings are not required for normal use cases but can address unique requirements or provide additional functionality. Multiple properties can be defined in a semicolon-separated list.

Specify multiple properties in a semicolon-separated list.

Integration and Formatting

Pagesize

Specifies the maximum number of items provider evaluates per API request. The default value, -1, allows the server to calculate the page size automatically.

Data Type

int

Default Value

-1

Remarks

Note that this limit applies to the number of items evaluated, not the number of matching items returned. If the dataset size exceeds 1 MB or the number of evaluated items reaches the specified page size, the operation stops and returns the matching results along with a pagination token to retrieve the remaining data. Set this property to a specific value to control the size of each API request and optimize performance. Adjust this property based on your application’s performance and memory requirements.

PseudoColumns

Specifies the pseudocolumns to expose as table columns. Use the format 'TableName=ColumnName;TableName=ColumnName'. The default is an empty string, which disables this property.

Data Type

string

Default Value

""

Remarks

This property allows you to define which pseudocolumns the connector exposes as table columns.

To specify individual pseudocolumns, use the following format: "Table1=Column1;Table1=Column2;Table2=Column3"

To include all pseudocolumns for all tables use: "*=*"

QueryMode

Specifies the mode used by the provider to retrieve results from Amazon DynamoDB.

Possible Values

Adaptive, PartiQL, SCAN

Data Type

string

Default Value

Adaptive

Remarks

This property determines the query execution strategy for retrieving results from DynamoDB:

• Adaptive: Automatically selects the best query mode based on the SQL statement filters and ThreadCount.
• PartiQL: Translates supported SQL statements into their PartiQL equivalents for execution.
• SCAN: Performs a full table scan, using parallel threads as specified by ThreadCount.

Use Adaptive for optimal performance, as it dynamically selects the most efficient query mode. Choose PartiQL for precise query translation or SCAN when a complete table scan is required.

RetryWaitTime

Specifies the minimum number of milliseconds the provider waits before retrying a request. The wait time doubles with each retry.

Data Type

string

Default Value

2000

Remarks

This property defines the base wait time, in milliseconds, between retries when a temporary issue is detected like a network failures or rate-limiting. With each retry, the wait time doubles, following an exponential backoff strategy.

The total number of retries is controlled by the MaximumRequestRetries property. For example, if RetryWaitTime is set to 2000 milliseconds and MaximumRequestRetries is set to 3, the driver waits 2000, 4000, and 8000 milliseconds before subsequent retries.

RowScanDepth

The maximum number of rows to scan to look for the columns available in a table.

Data Type

int

Default Value

50

Remarks

The columns in a table must be determined by scanning table rows. This value determines the maximum number of rows that will be scanned.

Setting a high value may decrease performance. Setting a low value may prevent the data type from being determined properly, especially when there is null data.

SeparatorCharacter

Specifies the character or characters used to denote hierarchy in flattened structures, such as Maps and List attributes in DynamoDB.

Data Type

string

Default Value

.

Remarks

This property defines the delimiter used to represent hierarchical relationships in flattened structures within DynamoDB. For example, when SeparatorCharacter is set to ".", an attribute named address.city indicates that address is a parent attribute with a child attribute called city.

If your data includes attribute names containing the specified separator, for example, a period (.), you should choose a different SeparatorCharacter to prevent ambiguity in column naming. This property is useful for handling complex, nested data structures where clear delineation of hierarchy is required.

ThreadCount

Specifies the number of threads to allocate for parallel scans during data selection. A value of 1 disables parallel scanning, while higher values increase parallelism.

Data Type

string

Default Value

5

Remarks

Parallel scans allow the retrieval process to run across multiple threads, improving performance when scanning large datasets in Amazon DynamoDB. The number of threads specified by ThreadCount determines how data is split for processing. While increasing ThreadCount can significantly speed up scans, it also accelerates the consumption of read units for the table.

Higher values for ThreadCount require more system resources, such as CPU cores and bandwidth. Excessive parallelism may exhaust read capacity units quickly, potentially incurring additional costs or impacting other operations on the table. It is important to evaluate your system’s available resources and the read units allocated to your DynamoDB tables before adjusting this property.

Timeout

Specifies the maximum time, in seconds, that the provider waits for a server response before throwing a timeout error. The default is 60 seconds. Set to 0 to disable the timeout.

Data Type

int

Default Value

60

Remarks

This property controls the maximum time, in seconds, that the connector waits for an operation to complete before canceling it. If the timeout period expires before the operation finishes, the connector cancels the operation and throws an exception.

The timeout applies to each individual communication with the server rather than the entire query or operation. For example, a query could continue running beyond the timeout value if each paging call completes within the timeout limit.

Setting this property to 0 disables the timeout, allowing operations to run indefinitely until they succeed or fail due to other conditions such as server-side timeouts, network interruptions, or resource limits on the server. Use this property cautiously to avoid long-running operations that could degrade performance or result in unresponsive behavior.

TypeDetectionScheme

Specifies the method used to determine the data type of columns.

Possible Values

None, RowScan

Data Type

string

Default Value

RowScan

Remarks

This property defines the strategy for determining column data types:

• None: All columns are returned as string types. Column names are still scanned when Header=True, even with this setting.
• RowScan: Rows are scanned to heuristically infer data types based on their content. The depth of the scan is controlled by the RowScanDepth property.

By default, RowScanDepth is used if no value is explicitly specified. Use None for simplicity when data type inference is not required or when consistent string typing is preferred.

UseBatchWriteItemOperation

Specifies the use of the BatchWriteItem operation for updates and inserts. This is required for handling binary or binary-set data, as the default operations (ExecuteStatement/BatchExecuteStatement) do not support these field types.

Data Type

bool

Default Value

false

Remarks

By default, the connector uses the ExecuteStatement or BatchExecuteStatement operation to handle updates and inserts. However, these operations do not support manipulating binary or binary-set fields. To handle these data types, enable this property to switch to the BatchWriteItem operation.

Using BatchWriteItem may alter the behavior and performance characteristics of updates and inserts. This property should only be enabled when your dataset includes binary or binary-set data that needs to be inserted or updated. For other use cases, the default operations are sufficient.

UseConsistentReads

Specifies whether consistent reads should always be used when querying DynamoDB. Consistent reads provide the most up-to-date data, but consume more read capacity.

Data Type

bool

Default Value

false

Remarks

When this property is set to true, the connector performs consistent reads, ensuring the most up-to-date data is returned for queries and scans. However, consistent reads consume twice as many read capacity units as eventually consistent reads. Use this property only when accurate and immediate data consistency is critical for your use case.

UserDefinedViews

Specifies a filepath to a JSON configuration file defining custom views. The provider automatically detects and uses the views specified in this file.

Data Type

string

Default Value

""

Remarks

This property allows you to define and manage custom views through a JSON-formatted configuration file called UserDefinedViews.json. These views are automatically recognized by the connector and enable you to execute custom SQL queries as if they were standard database views. The JSON file defines each view as a root element with a child element called "query", which contains the SQL query for the view. For example:

{
    "MyView": {
        "query": "SELECT * FROM Account WHERE MyColumn = 'value'"
    },
    "MyView2": {
        "query": "SELECT * FROM MyTable WHERE Id IN (1,2,3)"
    }

}

You can define multiple views in a single file and specify the filepath using this property. For example: UserDefinedViews=C:\Path\To\UserDefinedViews.json. When you use this property, only the specified views are seen by the connector.

Refer to User Defined Views for more information.

UseSimpleNames

Specifies whether or not simple names should be used for tables and columns.

Data Type

bool

Default Value

false

Remarks

Amazon DynamoDB tables and can use special characters in names that are normally not allowed in standard databases. UseSimpleNames makes the connector easier to use with traditional database tools.

Setting UseSimpleNames to True simplifies the names of columns returned. It also enforces a naming scheme such that only alphanumeric characters and the underscore are valid for the displayed column names.

Notes:

• Any non-alphanumeric characters are converted to underscores.
• If the column or table names exceed 128 characters in length they are truncated to 128 characters to comply with SQL Server standards.