Export Data from SQL Server to Google Cloud Storage through SSIS

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Google Cloud Storage SSIS Components

Powerful SSIS Source & Destination Components that allows you to easily connect SQL Server with Google Cloud Storage through SSIS Workflows.

Use the Google Cloud Storage Data Flow Components to synchronize with Google Cloud Storage Buckets, Objects, and more. Perfect for data synchronization, local back-ups, workflow automation, and more!



Easily push SQL Server data to Google Cloud Storage using the CData SSIS Tasks for Google Cloud Storage.

SQL Server databases are commonly used to store enterprise records. It is often necessary to move this data to other locations. The CData SSIS Task for Google Cloud Storage allows you to easily transfer Google Cloud Storage data. In this article you will export data from SQL Server to Google Cloud Storage.

Add Source and Destination Components

To get started, add a new ADO.NET Source control and a new Google Cloud Storage Destination control to the data flow task.

Configure the ADO.NET Source

Follow the steps below to specify properties required to connect to the SQL Server instance.

  1. Open the ADO.NET Source and add a new connection. Enter your server and database information here.
  2. In the Data access mode menu, select "Table or view" and select the table or view to export into Google Cloud Storage.
  3. Close the ADO NET Source wizard and connect it to the destination component.

Create a New Connection Manager for Google Cloud Storage

Follow the steps below to set required connection properties in the Connection Manager.

  1. Create a new connection manager: In the Connection Manager window, right-click and then click New Connection. The Add SSIS Connection Manager dialog is displayed.
  2. Select CData GoogleCloudStorage Connection Manager in the menu.
  3. Configure the connection properties.

    Authenticate with a User Account

    You can connect without setting any connection properties for your user credentials. After setting InitiateOAuth to GETANDREFRESH, you are ready to connect.

    When you connect, the Google Cloud Storage OAuth endpoint opens in your default browser. Log in and grant permissions, then the OAuth process completes

    Authenticate with a Service Account

    Service accounts have silent authentication, without user authentication in the browser. You can also use a service account to delegate enterprise-wide access scopes.

    You need to create an OAuth application in this flow. See the Help documentation for more information. After setting the following connection properties, you are ready to connect:

    • InitiateOAuth: Set this to GETANDREFRESH.
    • OAuthJWTCertType: Set this to "PFXFILE".
    • OAuthJWTCert: Set this to the path to the .p12 file you generated.
    • OAuthJWTCertPassword: Set this to the password of the .p12 file.
    • OAuthJWTCertSubject: Set this to "*" to pick the first certificate in the certificate store.
    • OAuthJWTIssuer: In the service accounts section, click Manage Service Accounts and set this field to the email address displayed in the service account Id field.
    • OAuthJWTSubject: Set this to your enterprise Id if your subject type is set to "enterprise" or your app user Id if your subject type is set to "user".
    • ProjectId: Set this to the Id of the project you want to connect to.

    The OAuth flow for a service account then completes.

Configure the Google Cloud Storage Destination

In the destination component Connection Manager, define mappings from the SQL Server source table into the Google Cloud Storage destination table and the action you want to perform on the Google Cloud Storage data. In this article, you will insert Buckets entities to Google Cloud Storage.

  1. Double-click the Google Cloud Storage destination to open the destination component editor.
  2. In the Connection Managers tab, select the connection manager previously created.
  3. In the Use a Table, menu, select Buckets. In the Action menu, select Insert.
  4. On the Column Mappings tab, configure the mappings from the input columns to the destination columns.

Run the Project

You can now run the project. After the SSIS Task has finished executing, data from your SQL table will be exported to the chosen table.