This integration is certified by Stitch. For support, contact Stitch support.
|Release status||Released||Supported by||Stitch|
|SSL connections||Supported||VPN Connections||Unsupported|
|Data selection||Tables and columns||View Replication||Unsupported|
MSSQL Setup Requirements
To set up MSSQL in Stitch, you need:
Permissions in MSSQL that allow you to create/manage users. This is required to create the Stitch database user.
A server that:
- Uses case-insensitive collation. More info about collation can be found here in Microsoft’s documentation.
- 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: Whitelist Stitch's IP addresses
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:
Step 2: Create a Stitch database user
Creating a user with
SELECT privileges can either be done via a query or the MSSQL 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.
- Log into your database.
Create a SQL login for the Stitch database user:
CREATE LOGIN [stitch_username] WITH PASSWORD=’[password]’ go
Grant the Stitch user access to the database:
USE [database] go
Create the Stitch database user and map them to the database:
CREATE USER [stitch_username] FOR LOGIN go
Grant the Stitch user
SELECTprivileges to all tables in the database, run this command:
GRANT SELECT to [stitch_username] go
If you wish to limit the Stitch user to specific tables, run this command instead:
GRANT SELECT ON [schema_name].[table_name] TO [stitch_username] go
Step 3: Connect Stitch
- Sign into your Stitch account, if you haven’t already.
- On the Stitch Dashboard page, click the Add Integration button.
- Click the MSSQL 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 data warehouse.
For example, the name “Stitch MSSQL” would create a schema called
stitch_mssqlin the data warehouse. Note: The schema name cannot be changed after the integration is saved.
Host (Endpoint): Enter the host address (endpoint) used by the MSSQL instance.
In general, this will be
127.0.0.1(localhost), but could also be some other network address (ex:
184.108.40.206) or your server’s public IP address. Note: This must be the actual address - entering
localhostinto this field will cause connection issues.
Port: Enter the port used by the MSSQL instance. The default is
Username: Enter the Stitch MSSQL database user’s username.
Password: Enter the password for the Stitch 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.
In addition, 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: 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.
Stitch offers two methods of creating a replication schedule:
- Replication Frequency: This method requires selecting the interval you want replication to run for the integration. Start times of replication jobs are based on the start time and duration of the previous job. Refer to the Replication Frequency documentation for more information and examples.
Anchor scheduling: Based on the Replication Frequency, or interval, you select, this method “anchors” the start times of this integration’s replication jobs to a time you select to create a predictable schedule. Anchor scheduling is a combination of the Anchor Time and Replication Frequency settings, which must both be defined to use this method. Additionally, note that:
- A Replication Frequency of at least one hour is required to use anchor scheduling.
An initial replication job may not begin immediately after saving the integration, depending on the selected Replication Frequency and Anchor Time. Refer to the Anchor Scheduling documentation for more information.
- You’ll need to contact support to request using an Anchor Time with this integration.
To help prevent overages, 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 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 track 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.
- After you set a table to replicate, the Table Settings page will display. Note: When you track a table, by default all columns will also be tracked.
In the Table 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.
Initial and historical replication jobs
After you finish setting up MSSQL, 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.
Extracting data from MSSQL
When you connect a database as an input, Stitch only needs read-only access to the databases, tables, and columns you want to replicate. There are two processes Stitch runs during the Extraction phase of the replication process: a structure sync and a data sync.
This is the first part of the Extraction process. During this phase, Stitch will detect any changes to the structure of your database. For example: A new column is added to one of the tables you set to replicate in Stitch. Structure syncs are how Stitch identifies the databases, tables, and columns to display in the Stitch app.
Stitch runs the following queries on MSSQL databases to perform a structure sync:
SELECT [database_name] FROM sys.sysdatabases
SELECT [table_name] FROM [database_name].information_schema.tables
This is the second part of the Extraction process. During this phase, Stitch extracts data from the source and replicates it. The method Stitch uses is the same for all databases, but differs depending on the Replication Method that each table uses.
The tabs below contain info about the queries Stitch runs during the data syncs for each type of Replication Method supported for MSSQL integrations.
Data syncs for tables using Key-based Incremental
Initial (historical) replication jobs
During the initial replication job for a table using Key-based Incremental Replication, Stitch will replicate the table in full by running a
SELECT query and read out of the resulting cursor in batches:
SELECT column_a, column_b <,...> FROM table_a ORDER BY replication_key_column
Ongoing replication jobs
During subsequent jobs, Stitch will use the last saved maximum value of the Replication Key column to identify new and updated data.
Stitch will run the following query and read out of the associated cursor in batches:
SELECT column_a, column_b <,...> FROM table_a WHERE replication_key_column >= 'last_maximum_replication_key_value' ORDER BY replication_key_column
Data syncs for tables using Full Table
For tables using Full Table Replication, Stitch runs a single query and reads out of the resulting cursor in batches:
SELECT column_a, column_b <,...> FROM table_a
This query will be run for each table using Full Table Replication during every replication job, whether it's the initial historical job or a subsequent job.
While we make every effort to ensure the queries that Stitch executes don’t impart significant load on your databases, we still have some recommendations for guaranteeing database performance:
- Use a replica database instead of connecting directly. We recommend using read replicas in lieu of directly connecting production databases with high availability and performance requirements.
- Apply indexes to Replication Key columns. We restrict and order our replication queries by this column, so applying an index to the columns you’re using as Replication Keys can improve performance.
Connection issues and collation
If you’re experiencing connection issues and have verified that the database user has the correct permissions, check your server’s collation setting.
Connecting MSSQL to Stitch successfully requires that your server use case-insensitive collation.
Data discrepancies and database user language settings
If you’re missing data, check that the database user’s language setting is set to
us_english. Using a different setting can cause problems with replication, including issues with properly identifying new and updated data.