This integration is powered by Singer's Microsoft Azure SQL Database tap and certified by Stitch. Check out and contribute to the repo on GitHub.
For support, contact Stitch support.
Microsoft Azure SQL Database feature snapshot
A high-level look at Stitch's Microsoft Azure SQL Database (v1) integration, including release status, useful links, and the features supported in Stitch.
Released on July 12, 2019
|Singer GitHub repository|
|Configurable Replication Methods||
|Full Table Replication||
Connecting Microsoft Azure SQL Database
Microsoft Azure SQL Database setup requirements
To set up Microsoft Azure SQL Database in Stitch, you need:
Privileges in Microsoft Azure SQL Database 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 the
ALTER DATABASEprivilege in Microsoft Azure SQL Database. This is required to complete the setup for Log-based Incremental Replication.
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 from Stitch to be successful, you’ll need to configure the firewall for your instance to allow access from our IP addresses.
Sign into your Microsoft Azure portal.
- Locate and open the database you want to connect to Stitch.
Click Settings > Connection security.
- For each of Stitch’s IP addresses listed below, create a rule:
- Rule name: Enter a name for the rule. For example:
- Start IP: Paste one of Stitch’s IP addresses.
- End IP: Paste the same IP address.
Stitch’s IP addresses are:
- Rule name: Enter a name for the rule. For example:
- Click the three dots to the right of the End IP field to add the rule.
Repeat steps 4 and 5 until there is a rule for each IP address. The screen should look similar to the following when you’re finished:
Note: You may also want to add your own IP address(es) to this list. This ensures that you’ll also be able to connect to the database as needed.
- Click Save.
- Follow the steps in the Setting up an SSH Tunnel for a Microsoft Azure database guide to set up an SSH tunnel for Microsoft Azure SQL Database.
- 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 Azure SQL Database. 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 Azure SQL Database UI. In this section, we’ll walk you through using the query method.
Depending on your setup and the access you grant to the Stitch database user, you may need to create several Microsoft Azure SQL Database integrations to allow Stitch to replicate all your data. This is due to a Microsoft Azure SQL Database limitation on how access is granted to
If the Stitch user has access to the master database and this database is then used for authentication, you can replicate all databases that the user has access to from a single Microsoft Azure SQL Database integration setup.
If the database you’re replicating isn’t the master database, you’ll only be able to replicate schemas and tables within that database. This will require creating additional Microsoft Azure SQL Database integrations in Stitch.
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_login> WITH PASSWORD='<password>'; CREATE USER <stitch_username> FOR LOGIN <stitch_login>; GO
Grant the Stitch user
SELECTprivileges by running this command for every table you want to replicate:
GRANT SELECT ON <schema_name>.<table_name> TO <stitch_username>; GO
Limiting access to only the tables you want to replicate ensures that the integration can complete discovery (a structure sync) in a timely manner. If you encounter issues in Stitch where tables aren’t displaying, try limiting the Stitch database user’s table access.
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>; GO
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 Azure SQL Database 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 Azure SQL Database 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 Azure SQL Database” would create a schema called
stitch_microsoft_azure_sql_databasein 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 Azure SQL Database instance. This is usually a server endpoint like
Port: Enter the port used by the instance. The default is
Username: Enter the Stitch Microsoft Azure SQL Database user’s username. We recommend copying and pasting the username Microsoft Azure SQL Database displays to you directly into this field. Note: Verify that the name includes
'@domain'or you’ll run into connection issues.
Password: Enter the password for the Stitch Microsoft Azure SQL Database 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.
Note: If this field is defined, Stitch will attempt to connect to only the database entered. If undefined, Stitch will attempt to connect to all of the databases the Stitch user has access to. To connect several specific databases, create an integration for each database you want to connect and define it in this field.
Step 4.2: Define the SSH connection details
If you’re using an SSH tunnel to connect your Microsoft Azure SQL Database database to Stitch, you’ll also need to define the SSH settings. Refer to the Setting up an SSH Tunnel for a Microsoft Azure database 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: Define Log-based Replication setting
In the Log-based Replication section, you can set this as the integration’s default Replication Method.
When enabled, tables that are set to replicate will use Log-based Incremental Replication by default. If you don’t want a table to use Log-based Incremental Replication, you can change it in the Table Settings page for that table.
If this setting isn’t enabled, you’ll have to select a Replication Method for each table you set to replicate.
Step 4.5: 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 Azure SQL Database 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 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 Azure SQL Database, 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.