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Add the SQL Server Connector

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Authenticate to SQL Server

supports authenticating to in several ways. Select your authentication method below to proceed to the relevant section that contains the authentication details.

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Password

To connect with your user credentials, specify the following properties:
  • Auth Scheme: Select Password.
  • User: Enter the username that you use to authenticate to .
  • Password: Enter the password that you use to authenticate to .

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NTLM

To connect with your NTLM user credentials, specify the following properties:
  • Auth Scheme: Select NTLM.
  • User: Enter the username that you use to authenticate to .
  • Password: Enter the password that you use to authenticate to .
  • (Optional) Domain: Enter the name of the domain for a Windows (NTLM) security login.
  • (Optional) NTLM Version: Select the NTLM version that you want to use. The default version is 1.

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Kerberos

To connect with your Kerberos credentials, specify the following properties:
  • Auth Scheme: Select Kerberos.
  • User: Enter the username that you use to authenticate to .
  • Password: Enter the password that you use to authenticate to .
  • Kerberos KDC: Enter the this to the host name or IP Address of your Kerberos Key Distribution Center (KDC) machine.
  • Kerberos Realm: Enter the Kerberos realm that you use to authenticate to Kerberos.
  • Kerberos SPN: Enter the service principal name (SPN) for the Kerberos domain controller.
  • (Optional) Kerberos Keytab File: Enter the full file path to your Kerberos keytab file.
  • (Optional) Kerberos Ticket Cache: Enter the full file path to an MIT Kerberos credential cache file.

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AzurePassword

To connect with your Azure user credentials, specify the following properties:
  • Auth Scheme: Select AzurePassword.
  • User: Enter the username that you use to authenticate to Azure.
  • Password: Enter the password that you use to authenticate to Azure.

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Azure Active Directory

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Azure Managed Service Identity

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Azure Service Principal

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Azure Service Principal Certificate

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Complete Your Connection

To complete your connection:
  1. For the Database property (optional), enter the default database to which you want to connect when you connect to .

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Set Up SQL Server for Change Data Capture

supports two methods for tracking the changes from your source database:
  • Change data capture (CDC): Change data capture tracks every change that is applied to a table and records those changes in a shadow history table. Rather than capturing only the primary key (for example, Change Tracking), CDC records the full row data to the history table.
  • Change tracking: Change tracking provides an efficient tracking mechanism for . Once change tracking is configured on your tables, any DML statement that affects rows in the source table causes change-tracking information to be recorded to the change-tracking table for each modified row.
If both of these methods are enabled on a table, uses CDC.
Follow the steps in the relevant section to set up your preferred method.

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Enable Change Data Capture for CData Sync

To use CDC for the source in , ensure that you have the following prerequisites in place:
  • CDC must be enabled on the database.
  • The agent must be running.
  • You must be a member of the db_owner fixed database role for the database.
After you verify these prerequisites, enable CDC on your database by submitting the following statements:
To enable CDC on an individual table, submit the following statements:

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Enable Change Tracking for CData Sync

You can enable change tracking on a database or on individual tables. To enable change tracking on your database, submit the following statement:
The CHANGE_RETENTION parameter specifies the time period for which change-tracking information is kept in your database. As a best practice, set a longer time frame to give time to resolve conflicts and errors. If the last successful job run is outside the retention period, replicates the full table automatically to ensure that no changes are missed. To enable change tracking on an individual table, submit the following statement:
To use change tracking, each table must have at least one primary key.

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Alter Schema

The way that handles schema changes for source tables depends on whether you use CDC or change tracking.

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Change Data Capture

When you use CDC, supports seamless transitions between CDC capture instances after a schema change, allowing replication to continue without data loss or a full refresh. Because does not track new columns on an existing capture instance, apply schema changes as follows:
  1. Alter the schema of the source table.
  2. Create a new CDC capture instance by running the sys.sp_cdc_enable_table stored procedure with a new @capture_instance name. runs the old and new capture instances in parallel. At the start of the next CDC job run, detects the new capture instance and continues reading from the original instance until all changes up to the new instance’s starting log sequence number (min_lsn) are processed. then switches to the new capture instance automatically and updates its stored CDC metadata.
After completes the transition, you can safely remove the old capture instance by running sys.sp_cdc_disable_table. This feature is supported for standard CDC replication and CDC replication with History Mode enabled.
  • supports a maximum of two concurrent capture instances per table. If detects more than two instances, it generates an error.
  • Do not remove the original capture instance until has completed the transition. If the original instance is dropped too early, the job fails because still needs to read the remaining changes from it.

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Change Tracking

When you use change tracking, updates the destination table automatically when changes (like adding a column or changing a data type) are made to the source table structure.

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Support for Incremental Replication

The source supports incremental replication. Incremental replication reduces the workload tremendously and minimizes bandwidth use and latency of synchronization. Moving data in increments offers great flexibility when you are dealing with slow APIs or daily quotas. You must configure the incremental check column based on the source columns. For details about how to set up incremental replication, see Incremental Replication.

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Always Encrypted Support

connects to sources by using the CData JDBC driver. The JDBC driver supports Always Encrypted columns, which enables to read data from columns that use client-side encryption. When reads from Always Encrypted columns, the JDBC driver returns decrypted plaintext values instead of binary or hexadecimal representations. This behavior allows encrypted columns to be included in replication workflows without causing read failures.

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