Microsoft Azure SQL Database (v1) | Stitch Documentation

Microsoft Azure SQL Database extraction is supported by Stitch
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 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.

STITCH
Release status	Released on July 12, 2019	Supported by	[Stitch] (https://community.qlik.com/t5/Support/ct-p/qlikSupport)
Stitch plan	Standard	Supported versions
API availability	Available	Singer GitHub repository	singer-io/tap-mssql
CONNECTION METHODS
SSH connections	Supported	SSL connections	Supported
REPLICATION SETTINGS
Anchor Scheduling	Supported	Advanced Scheduling	Supported
Table-level reset	Supported	Configurable Replication Methods	Supported
REPLICATION METHODS
Log-based Replication	Supported	Key-based Replication	Supported
Full Table Replication	Supported
DATA SELECTION
Table selection	Supported	Column selection	Supported
View replication	Supported	Select all	Supported, with prerequisites
TRANSPARENCY
Extraction Logs	Supported	Loading Reports	Supported

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 DATABASE privilege in Microsoft Azure SQL Database. This is required to complete the setup for Log-based Incremental Replication.
- A Primary Key in the source table. This is required to use logical replication.

Step 1: Verify your Stitch account's data pipeline region

First, you’ll log into Stitch and verify the data pipeline region your account is using. Later in this guide, you’ll need to grant Stitch access by whitelisting our IP addresses.

The IP addresses you’ll whitelist depend on the Data pipeline region your account is in.

Sign into your Stitch account, if you haven’t already.
Click User menu (your icon) > Edit User Settings and locate the Data pipeline region section to verify your account’s region.
Locate the list of IP addresses for your region:
- North America region IP addresses
- Europe region IP addresses

Keep this list handy - you’ll need it later.

Step 2: 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.

I'm using a direct connection.

For the connection from Stitch to be successful, you’ll need to configure the firewall for your instance to allow access from IP addresses for your Stitch data pipeline region.

Sign into your Microsoft Azure portal.
Locate and open the database you want to connect to Stitch.
Click Settings > Connection security.
For each of the IP addresses you retrieved in Step 1 for your Stitch data pipeline region, create a rule:
- Rule name: Enter a name for the rule. For example: Stitch<number>
- Start IP: Paste one of the Stitch data pipeline region IP addresses.
- End IP: Paste the same IP address.
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 for your Stitch data pipeline region. Below is an example of what this might look like using Stitch’s North America IP addresses:

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.

I'm using an SSH tunnel to connect.

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 3: Enable Log-based Incremental Replication with Change Tracking

Note: Skip this step if you’re not planning to use Log-based Incremental Replication. Click to skip ahead.

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 3.1: Verify database compatibility
Step 3.2: Enable change tracking for the database
Step 3.3: Enable change tracking for tables

Step 3.1: Verify database compatibility

Note: The SELECT from sys.databases and ALTER DATABASE privileges 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 90.

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 90 or the CHANGETABLE function (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 3.2: Enable change tracking for the database

Note: You must have the ALTER DATABASE privilege 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 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 Azure SQL Database. 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 3.3: 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 4: 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

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 sys.database views.

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.

Important: This user’s language setting must be set to 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 SELECT privileges 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
SELECT	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 5: Connect Stitch

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

Step 5.1: Define the database connection details
Step 5.2: Define the SSH connection details
Step 5.3: Define the SSL connection details
Step 5.4: Define Log-based Replication setting
Step 5.5: Create a replication schedule

Step 5.1: 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_database 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 Azure SQL Database instance. This is usually a server endpoint like <server-name>.database.windows.net.
- Port: Enter the port used by the Microsoft Azure SQL Database instance. The default is 1433.
- 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.
- **: **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.
- Include Microsoft SQL Server schema names in destination tables: Checking this setting will include schema names from the source database in the destination table name - for example: <source_schema_name>__<table_name>.
  
  Stitch loads all selected replicated tables to a single schema, preserving only the table name. If two tables canonicalize to the same name - even if they’re in different source databases or schemas - name collision errors can arise. Checking this setting can prevent these issues.
  
  Note: This setting can not be changed after the integration is saved. Additionally, this setting may create table names that exceed your destination’s limits. For more info, refer to the Database Integration Table Name Collisions guide.

Step 5.2: Define the SSH connection details

Note: Skip this step if you’re not using SSH to connect to Stitch.

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. (22 by default)
- SSH User: Enter the Stitch Linux (SSH) user’s username.

Step 5.3: Define the SSL connection details

Note: Skip this step if you’re not using SSL to connect to Stitch.

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 5.4: Define Log-based Replication setting

Note: Skip this step if you’re not planning to use Log-based Incremental Replication. Click to skip ahead.

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 5.5: Create a replication schedule

Replication schedules affect the time Extraction begins, not the time to data loaded. Refer to the Replication Scheduling documentation for more information.

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:

Replication Frequency
Anchor Scheduling
Advanced Scheduling using Cron (Advanced or Premium plans only)

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 6: Select data to replicate

Is an object missing or not replicating? Verify that the object meets the requirements for selection and replication.

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

Note: If a replication job is currently in progress, new selections won’t be used until the next job starts.

For Microsoft Azure SQL Database integrations, you can select:

Individual tables and columns
All tables and columns (except views)
Database views

Click the tabs to view instructions for each selection method.

In the Integration Details page, click the Tables to Replicate tab.
Locate a table you want to replicate.
Click the checkbox next to the table’s name. A blue checkmark means the table is set to replicate.
After you set a table to replicate, a page with the table’s columns will display. De-select columns if needed.
Next, you’ll define the table’s Replication Method. Click the Table Settings button.
In the Table Settings page:
1. Define the table’s Replication Method.
2. If using Key-based Incremental Replication, select a Replication Key.
3. When finished, click Update Settings.
Repeat this process for every table you want to replicate.
Click the Finalize Your Selections button at the bottom of the page to save your data selections.

Important: Before using this feature, note that:

Using the Select All feature will overwrite any previous selections. However, selections aren’t final until Finalize Your Selections is clicked. Clicking Cancel will restore your previous selections.
Log-based Incremental Replication must be enabled and set as the default Replication Method to use the Select All feature.

Refer to the Select All guide for more info about this feature.

Click into the integration from the Stitch Dashboard page.
Click the Tables to Replicate tab.
Navigate to the table level, selecting any databases and/or schemas that contain tables you want to replicate.
In the list of tables, click the box next to the Table Names column.
In the menu that displays, click Track AllTables and Fields (Except Views):
Click the Finalize Your Selections button at the bottom of the page to save your data selections.

Setting a database view to replicate is similar to selecting a table, with a few differences. Refer to the Replicating Database Views guide for detailed instructions.

At a high level, you’ll need to complete the following to select a database view:

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.

Replication will continue after the seven days are over. If you’re no longer interested in this source, be sure to pause or delete the integration to prevent unwanted usage.

Questions? Feedback?

Did this article help? If you have questions or feedback, feel free to submit a pull request with your suggestions, open an issue on GitHub, or reach out to us.

Related	Troubleshooting
Destination & Integration Compatibility Replication Scheduling Replication Methods Replication Keys	Database Connection Errors Understanding & Reducing Your Usage Re-Authorizing Integrations Replication Issues