Google Cloud SQL for SQL Server Setup Guide

Follow these instructions to replicate your Google Cloud SQL for SQL Server database to your destination using Fivetran.

Prerequisites

To connect your Google Cloud SQL for SQL Server database to Fivetran, you need:

A Google Cloud SQL for SQL Server database instance. If you don't have one, follow Google Cloud's create instance instructions.
SQL Server 2012 - 2022
Your database host's IP (e.g., 1.2.3.4) or domain (your.server.com)
Your database's port (usually 1433)

IMPORTANT: We do not support single-user mode.

Setup instructions

IMPORTANT: Do not perform the Choose connection method step if you want to use Hybrid Deployment for your data pipeline.

Choose connection method

Decide whether to connect your Google Cloud SQL for SQL Server database to Fivetran directly, using an SSH tunnel, or using Google Cloud Private Service Connect.

Connect directly (TLS required)

IMPORTANT: You must have TLS enabled on your database to connect directly to Fivetran. Follow Google Cloud's TLS setup instructions to enable TLS on your database.

Fivetran connects directly to your database instance. This is the simplest connection method.

To connect directly, configure your firewall and/or other access control systems to allow incoming connections to your SQL server host and port (usually 1433) from Fivetran's IPs for your database's region.

Connect using SSH (TLS optional)

Fivetran connects to a separate server in your network that provides an SSH tunnel to your database. You must connect through SSH if your database is in an inaccessible subnet.

To connect using SSH, do the following:

In your connector setup form, select Connect via an SSH tunnel to expose Fivetran's public SSH key. Copy the key by clicking the blue clipboard icon.
Add the public key to the authorized_keys file of your SSH server. The key must be all on one line, so make sure that you don't introduce any line breaks when cutting and pasting.
If you want Fivetran to tunnel SSH over TLS, follow Google Cloud's TLS setup instructions to enable TLS on your database.

Connect using Google Cloud Private Service Connect

IMPORTANT: You must have a Business Critical plan to use Google Cloud Private Service Connect.

NOTE: This connection method is in Beta.

Google Cloud Private Service Connect allows VPCs and Google-hosted or on-premises services to communicate with one another without exposing traffic to the public internet. Learn more in Google Cloud's Private Service Connect documentation.

Follow our Google Cloud Private Service Connect setup guide to configure Private Service Connect for your database.

Enable database access

Grant Fivetran's data processing servers access to your database.

In your Google Cloud Platform SQL dashboard, click on your primary database.
In the left menu, go to the Connections tab.
In the Networking section, click Add network.
In the New network window, create a network for Fivetran. What you enter in the Network field depends on whether you're connecting directly or using an SSH tunnel.
- If you're connecting directly, enter Fivetran's IPs for your database's region.
- If you're connecting using an SSH tunnel, enter {your-ssh-tunnel-server-ip-address}/32.
When you've finished, click Done, then click Save. It will take a few minutes for the database to be updated with the new settings.
In the left menu, go to the Overview tab.
In the Connect to this instance section, find your database's public IP address and make a note of it. You will need it to configure Fivetran.

Create user

Create a database user for Fivetran's exclusive use.

Open a connection to your Google Cloud SQL for SQL Server primary database in a SQL Server console (such as a SQL workbench, DataGrip, or mssql).
Create a login for Fivetran by executing the following SQL command. Replace <login_username> and some-password with a username and password of your choice.
```
CREATE LOGIN <login_username> with password = '<some-password>';
```
Create a user from the login you created. Replace <user_username> with a username of your choice.
```
CREATE USER <user_username> from login <login_username>;
```

Grant user permissions

Grant the Fivetran user SELECT permission for the databases, schemas, tables, or specific columns you want Fivetran to sync.

You can grant access to everything in a given database:

GRANT SELECT on DATABASE::<database> to <username>;

or all tables in a given schema:

GRANT SELECT on SCHEMA::<schema> to <username>;

or a specific table:

GRANT SELECT ON [<schema>].[<table>] TO <username>;

or a set of specific columns in a table:

GRANT SELECT ON [<schema>].[<table>] ([<column 1>], [<column 2>], ...) TO <username>;

Enable incremental updates

For incremental updates, we use one of the following tracking mechanisms:

These mechanisms let Fivetran copy only the rows that have changed since the last data sync so we don't have to copy the whole table every time. Learn more in our updating data documentation.

Choose to enable change tracking, change data capture, or Fivetran Teleport Sync. Depending on whether you are connecting Fivetran to your primary instance or an availability group replica, you may be limited in the mechanism you can choose. See our Supported Configurations documentation for more information.

Change tracking

Expand for instructions

Enable change tracking at the database level:
```
ALTER DATABASE [<database>] 
SET CHANGE_TRACKING = ON 
(CHANGE_RETENTION = 7 DAYS, AUTO_CLEANUP = ON);
```
NOTE: While we recommend seven days of change retention, you can set your retention period as low as one day. However, a shorter retention period increases the risk that your logs will expire in between syncs, triggering an automatic full source re-sync.

Enable CT for each table you want to integrate:

ALTER TABLE [<schema>].[<table>] ENABLE CHANGE_TRACKING;

Grant the Fivetran user VIEW CHANGE TRACKING permission for each of the tables that have CT enabled:
```
GRANT VIEW CHANGE TRACKING ON [<schema>].[<table>] TO <username>;
```

Change data capture

Expand for instructions

Enable change data capture at the database level:

EXEC msdb.dbo.gcloudsql_cdc_enable_db '[<database>]'

Enable CDC for each table you want to Fivetran to sync:
```
EXEC sys.sp_cdc_enable_table  
@source_schema = [<schema>],
@source_name   = [<table>],
@role_name     = [<username>];
```
To check if CDC is enabled, run the query below:
```
EXEC sys.sp_cdc_enable_table
@source_schema = N'[<schema>]',
@source_name = N'[<table>]',
@role_name = N'CDC' 
```
NOTE: Fivetran only supports tables with a single CDC capture instance. Our syncs only include tables and columns that are present in a CDC instance. If you add new tables or columns, you must create a new CDC instance that includes them and delete the old instance.

Fivetran Teleport Sync

You do not need to do any additional configuration to use Fivetran Teleport Sync.

(Optional) Schema changes for change tracking (CT) and change data capture (CDC) Private Preview

By default, when you create a new table in your database, you must manually enable CT or CDC for that table before we can sync it. Additionally, if you add a new column to an existing CDC-enabled table, you must manually recreate the CDC capture instance before we can sync the column.

If you want Fivetran to automatically enable CT or CDC for newly created tables and to update CDC capture instances when a new column is added, install the following stored procedures on your database. If your connector contains only CT-enabled tables, then any subsequent new tables will be CT-enabled. If your connector has a mixture of CT- and CDC-enabled tables or contains CDC-enabled tables only, then we will enable CDC over CT by default.

Expand for instructions

Install the following script on your database. Before running the script, replace <database> with your database name.

NOTE: If you have configured your connector to "Allow columns", you can exclude the [dbo].[sp_ft_enable_cdc] and [dbo].[sp_ft_enable_change_tracking] stored procedures. If you have configured your connector to "Block All", you can exclude all the following stored procedures.

USE [<database>];

/****** Object:  StoredProcedure [dbo].[sp_ft_enable_cdc]    Script Date: 1/17/2024 11:12:55 PM ******/
SET ANSI_NULLS ON
GO
   
SET QUOTED_IDENTIFIER ON
GO
   
CREATE OR ALTER PROCEDURE [dbo].[sp_ft_enable_cdc]
   @TableList NVARCHAR(MAX),
   @FivetranUser NVARCHAR(MAX)
WITH EXECUTE AS OWNER -- Change to an appropriate sysadmin user
AS
BEGIN
   SET NOCOUNT ON;

   -- Table to store tables with results
   CREATE TABLE #ResultTables (TableName NVARCHAR(MAX), Result NVARCHAR(MAX));

   -- Enable CDC for each table
   DECLARE @TableName NVARCHAR(MAX);
   DECLARE @SqlStatement NVARCHAR(MAX);

   WHILE LEN(@TableList) > 0
   BEGIN
      -- Get the first table in the list
      SET @TableName = NULL;
      SET @TableName = SUBSTRING(@TableList, 1, CHARINDEX(',', @TableList + ',') - 1);

      -- Remove the processed table from the list
      SET @TableList = STUFF(@TableList, 1, LEN(@TableName) + 1, '');

      -- Build and execute the SQL statement to enable CDC for the table
      SET @SqlStatement = '
      BEGIN TRY
         EXEC sys.sp_cdc_enable_table
             @source_schema = ''' + PARSENAME(@TableName, 2) + ''',
             @source_name   = ''' + PARSENAME(@TableName, 1) + ''',
             @role_name     = ''' + @FivetranUser + ''';
         
         INSERT INTO #ResultTables (TableName, Result) VALUES (''' + @TableName + ''', ''Success'');
      END TRY
      BEGIN CATCH
         PRINT ERROR_MESSAGE();
         INSERT INTO #ResultTables (TableName, Result) VALUES (''' + @TableName + ''', ERROR_MESSAGE());
      END CATCH
      ';

     -- Execute the dynamic SQL statement
     EXEC sp_executesql @SqlStatement;
   END

   -- Return the list of tables with results
   SELECT * FROM #ResultTables;
      
   -- Drop the temporary table
   DROP TABLE #ResultTables;
END;
GO


/****** Object:  StoredProcedure [dbo].[sp_ft_enable_change_tracking]    Script Date: 1/17/2024 11:10:45 PM ******/
SET ANSI_NULLS ON
GO
   
SET QUOTED_IDENTIFIER ON
GO
   
CREATE OR ALTER PROCEDURE [dbo].[sp_ft_enable_change_tracking]
   @TableList NVARCHAR(MAX),
   @FivetranUser NVARCHAR(MAX)
WITH EXECUTE AS OWNER -- Change to an appropriate sysadmin user
AS
BEGIN
   SET NOCOUNT ON;
      
   -- Table to store tables with results
   CREATE TABLE #ResultTables (TableName NVARCHAR(MAX), Result NVARCHAR(MAX));
      
   -- Enable change tracking for each table
   DECLARE @TableName NVARCHAR(MAX);
   DECLARE @SqlStatement NVARCHAR(MAX);
      
   WHILE LEN(@TableList) > 0
   BEGIN
      -- Get the first table in the list
      SET @TableName = NULL;
      SET @TableName = SUBSTRING(@TableList, 1, CHARINDEX(',', @TableList + ',') - 1);
      
      -- Remove the processed table from the list
      SET @TableList = STUFF(@TableList, 1, LEN(@TableName) + 1, '');
         
      -- Build and execute the SQL statement to enable change tracking
      SET @SqlStatement = '
      BEGIN TRY
         ALTER TABLE ' + @TableName + ' ENABLE CHANGE_TRACKING;
         GRANT VIEW CHANGE TRACKING ON ' + @TableName + ' TO ' + @FivetranUser + ';
         INSERT INTO #ResultTables (TableName, Result) VALUES (''' + @TableName + ''', ''Success'');
      END TRY
      BEGIN CATCH
         PRINT ERROR_MESSAGE();
         INSERT INTO #ResultTables (TableName, Result) VALUES (''' + @TableName + ''', ERROR_MESSAGE());
      END CATCH
      ';
         
      -- Execute the dynamic SQL statement
      EXEC sp_executesql @SqlStatement;
   END
      
   -- Return the list of tables with results
   SELECT * FROM #ResultTables;
      
   -- Drop the temporary table
   DROP TABLE #ResultTables;
END;
GO

  
/****** Object:  StoredProcedure [dbo].[sp_ft_get_tables_with_ddl_changes]    Script Date: 1/30/2024 9:10:47 PM ******/
SET ANSI_NULLS ON
GO
   
SET QUOTED_IDENTIFIER ON
GO

CREATE OR ALTER PROCEDURE [dbo].[sp_ft_get_tables_with_ddl_changes]
   @TableList NVARCHAR(MAX),
   @ddlTime DATETIME = NULL -- New parameter for ddlTime
WITH EXECUTE AS OWNER -- Change to an appropriate sysadmin user
AS
BEGIN
   SET NOCOUNT ON;

   -- Declare a table variable to store the results
   DECLARE @ChangedTables TABLE (
      TableName NVARCHAR(MAX),
      DdlTime DATETIME
   );

   -- Split the comma-separated list into a table variable
   DECLARE @TableNames TABLE (
      TableName NVARCHAR(MAX)
   );
      
   INSERT INTO @TableNames (TableName)
   SELECT value
   FROM STRING_SPLIT(@TableList, ',');
      
   -- Check for DDL changes in cdc.ddl_history
   INSERT INTO @ChangedTables (TableName, DdlTime)
   SELECT
      tn.TableName,
      MAX(dh.ddl_time) AS LatestDdlTime
   FROM cdc.ddl_history dh
   INNER JOIN @TableNames tn ON CONCAT(OBJECT_SCHEMA_NAME(dh.source_object_id), '.', OBJECT_NAME(dh.source_object_id)) = tn.TableName
   WHERE @ddlTime IS NULL OR dh.ddl_time >= @ddlTime
   GROUP BY tn.TableName;
      
   -- Return the list of tables with the latest DDL changes
   SELECT TableName, DdlTime
   FROM @ChangedTables;
END;
GO



/****** Object:  StoredProcedure [dbo].[sp_ft_update_cdc]    Script Date: 1/31/2024 1:19:40 AM ******/
SET ANSI_NULLS ON
GO

SET QUOTED_IDENTIFIER ON
GO

CREATE OR ALTER PROCEDURE [dbo].[sp_ft_update_cdc]
   @TableName NVARCHAR(MAX),
   @FivetranUser NVARCHAR(MAX),
   @CaptureInstance NVARCHAR(MAX),
   @CapturedColumnList NVARCHAR(MAX)
WITH EXECUTE AS OWNER
AS
BEGIN
   SET NOCOUNT ON;

    -- Table to store tables with results
    CREATE TABLE #ResultTables (TableName NVARCHAR(MAX), Result NVARCHAR(MAX));

    DECLARE @SourceSchema NVARCHAR(MAX);
    DECLARE @SourceName NVARCHAR(MAX);

    BEGIN TRY
        -- Assign values to variables for PARSENAME function
        SET @SourceSchema = PARSENAME(@TableName, 2);
        SET @SourceName = PARSENAME(@TableName, 1);

        -- Step 1: Disable the current CDC instance
        EXEC sys.sp_cdc_disable_table
            @source_schema    = @SourceSchema,
            @source_name      = @SourceName,
            @capture_instance = @CaptureInstance;

        -- Step 2: Create a new CDC instance
        EXEC sys.sp_cdc_enable_table
            @source_schema        = @SourceSchema,
            @source_name          = @SourceName,
            @role_name            = @FivetranUser,
            @capture_instance     = @CaptureInstance,
            @captured_column_list = @CapturedColumnList

        -- Insert the result into the #ResultTables table
        INSERT INTO #ResultTables (TableName, Result) VALUES (@TableName, 'Success');
    END TRY
    BEGIN CATCH
        PRINT ERROR_MESSAGE();
        -- Insert the error message into the #ResultTables table
        INSERT INTO #ResultTables (TableName, Result) VALUES (@TableName, ERROR_MESSAGE());
    END CATCH;

    -- Return the list of tables with results
    SELECT * FROM #ResultTables;

    -- Drop the temporary table
    DROP TABLE #ResultTables;
END;
GO

Grant the Fivetran user execute permission.

USE [<database>];
GRANT EXECUTE ON dbo.sp_ft_enable_cdc to <username>;
GRANT EXECUTE ON dbo.sp_ft_enable_change_tracking to <username>;
GRANT EXECUTE ON dbo.sp_ft_get_tables_with_ddl_changes to <username>;
GRANT EXECUTE ON dbo.sp_ft_update_cdc to <username>;

Finish Fivetran configuration

In your connector setup form, enter a destination schema prefix. This prefix applies to each replicated schema and cannot be changed once your connector is created.
In the Host field, enter your database host's IP (for example, 1.2.3.4) or domain (for example, your.server.com).
Enter your database instance's port number. The port number is usually 1433.
Enter the Fivetran-specific user that you created in Step 3.
Enter the password for the Fivetran-specific user that you created in Step 3.
Enter the name of your database (for example, your_database).
(Hybrid Deployment only) If your destination is configured for Hybrid Deployment, the Hybrid Deployment Agent associated with your destination is pre-selected in the Select an existing agent drop-down menu. To use a different agent, select the agent of your choice, and then select the same agent for your destination.
(Not applicable to Hybrid Deployment) Choose your connection method. If you selected Connect via an SSH tunnel, copy or make a note of the Public Key and add it to the authorized_keys file while configuring the SSH tunnel, and provide the following information:
- SSH hostname (do not use a load balancer's IP address/hostname)
- SSH port
- SSH user
- If you enabled TLS on your database in Step 1, set the Require TLS through tunnel toggle to ON.
Choose your incremental update method.
Click Save & Test. Fivetran tests and validates our connection to your Google Cloud SQL for SQL Server database. Upon successful completion of the setup tests, you can sync your data using Fivetran.

Setup tests

Fivetran performs the following tests to ensure that we can connect to your Google Cloud SQL for SQL Server database and that it is properly configured:

The Connecting to SSH Tunnel Test validates the SSH tunnel details you provided in the setup form. It then checks that we can connect to your database using the SSH Tunnel. (We skip this test if you aren't connecting using SSH.)
The Connecting to Host Test validates the database credentials you provided in the setup form. The test verifies that the host is not private and then checks the connectivity to the host.
The Validating Certificate Test generates a pop-up window where you must choose which certificate you want Fivetran to use. It then validates that certificate and checks that we can connect to your database using TLS. (We skip this test if you're connecting using a Google Cloud Virtual Machine.)
The Connecting to Database Test checks that we can access your database.
The Checking statement_timeout Value Test checks that we can access your database's pg_settings table. It then verifies that the statement_timeout value is greater than 5 minutes.