Microsoft SQL Server (v1)

Microsoft SQL Server feature snapshot

A high-level look at Stitch's Microsoft SQL Server (v1.0) integration, including release status, useful links, and the features supported in Stitch.

Connecting Microsoft SQL Server

Microsoft SQL Server setup requirements

To set up Microsoft SQL Server in Stitch, you need:

• Privileges in Microsoft SQL Server that allow you to create/manage users. This is required to create the Stitch database user.

• If using Log-based Incremental Replication, you’ll need:

  • A database running Microsoft SQL Server 2008 or higher. Earlier versions of Microsoft SQL Server don’t include Change Tracking functionality which is required for Log-based Incremental Replication.
  • The ALTER DATABASE privilege in Microsoft SQL Server. This is required to complete the setup for Log-based Incremental Replication.

• A server that:

  • Allows connections over TCP/IP
  • Allows mixed mode authentication

Make sure your server is set up properly before continuing. If you need some help figuring out your hosting details, we recommend looping in a member of your engineering team.

Step 1: Configure database connection settings

In this step, you’ll configure the database server to allow traffic from Stitch to access it. There are two ways to connect your database:

• A direct connection will work if your database is publicly accessible.
• An SSH tunnel is required if your database isn’t publicly accessible. This method uses a publicly accessible instance, or an SSH server, to act as an intermediary between Stitch and your database. The SSH server will forward traffic from Stitch through an encrypted tunnel to the private database.

Click the option you’re using below and follow the instructions.

Step 2: Enable Log-based Incremental Replication with Change Tracking

While Log-based Incremental Replication is the most accurate and efficient method of replication, using this replication method may, at times, require manual intervention or impact the source database’s performance. Refer to the Log-based Incremental Replication documentation for more info.

You can also use one of Stitch’s other Replication Methods, which don’t require any database configuration. Replication Methods can be changed at any time.

• Step 2.1: Verify database compatibility

• Step 2.2: Enable change tracking for the database

• Step 2.3: Enable change tracking for tables

Step 2.1: Verify database compatibility

In this step, you’ll verify the database’s database’s compatibility level. This setting sets some database behaviors to be compatible with a specified version of SQL Server. To use Change Tracking, your database must have a compatibility level greater than 90.

1. Log into your database:

   USE <database_name>
   GO
   

2. Run the following query to retrieve the database’s current compatibility level:

   SELECT compatibility_level
   FROM sys.databases WHERE name = '<database_name>';
   GO
   

   According to Microsoft’s documentation, this value must be greater than 90 or the CHANGETABLE function (used to obtain change tracking info during replication) will return an error.

3. If the result is less than 90, you’ll need to increase it to enable Change Tracking.

   Note: Before changing this setting, you should understand how doing so could impact your database. Refer to Microsoft’s documentation for more info.

   Use the following command to set the database compatibility level:

   ALTER DATABASE <database_name>
   SET COMPATIBILITY_LEVEL = 100;
   GO
   

Step 2.2: Enable change tracking for the database

In this step, you’ll enable Change Tracking at the database level. Use the following command to enable Change Tracking, replacing <database_name> with the name of the database:

ALTER DATABASE <database_name>  
SET CHANGE_TRACKING = ON  
(CHANGE_RETENTION = 3 DAYS, AUTO_CLEANUP = ON)

This command also defines the CHANGE_RETENTION and AUTO_CLEANUP settings:

• CHANGE_RETENTION - This specifies the time period for which change tracking information is kept. Change tracking information older than the specified time period is periodically removed by Microsoft SQL Server. Stitch recommends a minimum of 3 days.

• AUTO_CLEANUP - This controls the cleanup task that removes old change tracking information. When OFF, the task will be disabled and old change tracking information will not be removed.

  Tip: If you encounter an issue with a table, change AUTO_CLEANUP to OFF to disable cleanup tasks. This will ensure change tracking info is retained, allowing Stitch Support to more thoroughly investigate.

Step 2.3: Enable change tracking for tables

For every table you want to replicate using Log-based Incremental Replication, you will need to enable change tracking. When change tracking is enabled, change tracking information will be maintained for all rows in the table affected by a DML operation.

Run the following command to enable change tracking for a table:

ALTER TABLE <schema_name>.<table_name>  
ENABLE CHANGE_TRACKING  
WITH (TRACK_COLUMNS_UPDATED = ON)

Repeat this step for every table you want to replicate using Log-based Incremental Replication.

Step 3: Create a Stitch database user

Next, you’ll create a dedicated database user for Stitch. This will ensure Stitch is visible in any logs or audits, and allow you to maintain your privilege hierarchy.

• Instructions
• Privileges list

GRANT VIEW CHANGE TRACKING ON <schema_name>.<table_name> TO <stitch_username>

Step 4: Connect Stitch

In this step, you’ll complete the setup by entering the database’s connection details and defining replication settings in Stitch.

Step 4.1: Define the database connection details

1. If you aren’t signed into your Stitch account, sign in now.

2. On the Stitch Dashboard page, click the Add Integration button.

3. Locate and click the Microsoft SQL Server icon.

4. Fill in the fields as follows:

   • Integration Name: Enter a name for the integration. This is the name that will display on the Stitch Dashboard for the integration; it’ll also be used to create the schema in your destination.

     For example, the name “Stitch Microsoft SQL Server” would create a schema called stitch_microsoft_sql_server in the destination. Note: The schema name cannot be changed after the integration is saved.

   • Host (Endpoint): Enter the host address (endpoint) used by the Microsoft SQL Server instance. For example: This could be a network address such as 192.68.0.1, or a server endpoint like dbname.hosting-provider.com.

   • Port: Enter the port used by the instance. The default is 1433.

   • Username: Enter the Stitch Microsoft SQL Server database user’s username.

   • Password: Enter the password for the Stitch Microsoft SQL Server database user.

   • Database: Optional: Enter the name of the default database Stitch will connect to. Stitch will ‘find’ all databases you give the Stitch user access to - a default database is only used to test and complete the connection.

Step 4.2: Define the SSH connection details

If you’re using an SSH tunnel to connect your Microsoft SQL Server database to Stitch, you’ll also need to define the SSH settings. Refer to the Setting up an SSH Tunnel for a database connection guide for assistance with completing these fields.

1. Click the Encryption Type menu.

2. Select SSH to display the SSH fields.

3. Fill in the fields as follows:

   • Remote Address: Enter the public IP address or hostname of the server Stitch will SSH into.

   • SSH Port: Enter the SSH port on your server. (22 by default)

   • SSH User: Enter the Stitch Linux (SSH) user’s username.

Step 4.3: Define the SSL connection details

Click the Connect using SSL checkbox if you’re using an SSL connection. Note: The database must support and allow SSL connections for this setting to work correctly.

Step 4.4: Create a replication schedule

In the Replication Frequency section, you’ll create the integration’s replication schedule. An integration’s replication schedule determines how often Stitch runs a replication job, and the time that job begins.

Microsoft SQL Server integrations support the following replication scheduling methods:

• Replication Frequency

• Anchor Scheduling

To keep your row usage low, consider setting the integration to replicate less frequently. See the Understanding and Reducing Your Row Usage guide for tips on reducing your usage.

Step 4.5: Save the integration

When finished, click Save Integration.

Stitch will perform a connection test to the Microsoft SQL Server database; if successful, a Success! mesage will display at the top of the screen. Note: This test may take a few minutes to complete.

Step 5: Select data to replicate

The last step is to select select the tables and columns you want to replicate.

When you track a table, you’ll also need to define its Replication Method and, if using Key-based Incremental Replication, its Replication Key.

You can select tables and columns by:

1. In the Integration Details page, click the Tables to Replicate tab.
2. Locate a table you want to replicate.
3. Click the checkbox next to the object’s name. A green checkmark means the object is set to replicate.
4. If there are child objects, they’ll automatically display and you’ll be prompted to select some.

5. After you set a table to replicate, the Settings page will display. Note: When you track a table, by default all columns will also be tracked.

6. In the Settings page, define the table’s Replication Method and, if using Key-based Incremental Replication, its Replication Key.

7. Repeat this process for every table you want to replicate.

Initial and historical replication jobs

After you finish setting up Microsoft SQL Server, its Sync Status may show as Pending on either the Stitch Dashboard or in the Integration Details page.

For a new integration, a Pending status indicates that Stitch is in the process of scheduling the initial replication job for the integration. This may take some time to complete.

Free historical data loads

The first seven days of replication, beginning when data is first replicated, are free. Rows replicated from the new integration during this time won’t count towards your quota. Stitch offers this as a way of testing new integrations, measuring usage, and ensuring historical data volumes don’t quickly consume your quota.

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