This integration is powered by Singer's Microsoft SQL Server tap and certified by Stitch. Check out and contribute to the repo on GitHub.
For support, contact Stitch support.
Microsoft SQL Server feature snapshot
A high-level look at Stitch's Microsoft SQL Server (v1) integration, including release status, useful links, and the features supported in Stitch.
Released on July 12, 2019
2012 through 2017
|Singer GitHub repository|
|Configurable Replication Methods||
|Full Table Replication||
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.
A database running Microsoft SQL Server version 2012 through 2017. Microsoft SQL Server 2012 is the miminum version that Stitch supports for this type of integration.
If using Log-based Incremental Replication, you’ll need:
ALTER DATABASEprivilege 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.
For the connection to be successful, you’ll need to configure your firewall to allow access from our IP addresses. Whitelist the following IPs before continuing onto the next step:
- Follow the steps in the Setting up an SSH Tunnel for a database connection guide to set up an SSH tunnel for Microsoft SQL Server.
- Complete the steps in this guide after the SSH setup is complete.
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
ALTER DATABASEprivileges are required to complete this step.
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
Log into your database:
USE <database_name> GO
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
CHANGETABLEfunction (used to obtain change tracking info during replication) will return an error.
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
ALTER DATABASEprivilege to complete this step.
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- 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
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
OFFto 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.
Creating a user with
SELECT privileges can either be done via a query or the Microsoft SQL Server UI. In this section, we’ll walk you through using the query method.
us_english. Issues with replication may arise if a different setting is used.
Create the Stitch database user, replacing
<database_name>with the name of the database and
<password>with a secure password:
USE <database_name> CREATE LOGIN <stitch_username> WITH PASSWORD='<password>' CREATE USER <stitch_username> FOR LOGIN
Grant the Stitch user
SELECTprivileges. To grant
SELECTprivileges to all tables in the database, run this command:
GRANT SELECT to <stitch_username>
If you want to limit the Stitch user to specific tables, run this command instead:
GRANT SELECT ON <schema_name>.<table_name> TO <stitch_username>
Note: Column-level permissions are not supported for use with Log-based Incremental Replication. Restricting access to columns will cause replication issues.
Important: Using Log-based Incremental Replication
Additionally, if you want to use Log-based Incremental Replication, you’ll also need to grant the Stitch user
VIEW TRACKING CHANGES privileges on the tables where change tracking is enabled:
GRANT VIEW CHANGE TRACKING ON <schema_name>.<table_name> TO <stitch_username>
For every table you want to replicate, you’ll need to run this command.
See the Privileges list tab for an explanation of why these permissions are required by Stitch.
In the table below are the database user privileges Stitch requires to connect to and replicate data from a Microsoft SQL Server database.
|Privilege name||Reason for requirement|
Required to select rows from tables in a database.
|VIEW CHANGE TRACKING||
Required to use Log-based Incremental Replication. Required to obtain change tracking information from tables where change tracking is enabled.
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
- If you aren’t signed into your Stitch account, sign in now.
On the Stitch Dashboard page, click the Add Integration button.
- Locate and click the Microsoft SQL Server icon.
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_serverin 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
126.96.36.199, or a server endpoint like
Port: Enter the port used by the instance. The default is
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.
Click the SSH Tunnel checkbox.
Fill in the fields as follows:
SSH Host: Enter the public IP address or hostname of the server Stitch will SSH into.
SSH Port: Enter the SSH port on your server. (
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:
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 Check and Save.
Stitch will perform a connection test to the Microsoft SQL Server database; if successful, a Success! message 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.
You can select tables and columns by:
- In the Integration Details page, click the Tables to Replicate tab.
- Locate a table you want to replicate.
- Click the checkbox next to the object’s name. A green checkmark means the object is set to replicate.
If there are child objects, they’ll automatically display and you’ll be prompted to select some. Note: When you track a table, by default all columns will also be tracked.
After you set a table to replicate, a page with the table’s columns will display. De-select columns if needed.
In the Settings page, define the table’s Replication Method and, if using Key-based Incremental Replication, its Replication Key.
Repeat this process for every table you want to replicate.
- Click the Finalize Your Selections button to save your data selections.
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.
Initial replication jobs with Anchor Scheduling
If using Anchor Scheduling, an initial replication job may not kick off immediately. This depends on the selected Replication Frequency and Anchor Time. Refer to the Anchor Scheduling documentation for more information.
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.