Automated Continuous Azure Data Lake Storage Replication to Google BigQuery


Use CData Sync for automated, continuous, customizable Azure Data Lake Storage replication to Google BigQuery.

Always-on applications rely on automatic failover capabilities and real-time data access. CData Sync integrates live Azure Data Lake Storage data into your Google BigQuery instance, allowing you to consolidate all of your data into a single location for archiving, reporting, analytics, machine learning, artificial intelligence and more.

Configure Google BigQuery as a Replication Destination

Using CData Sync, you can replicate Azure Data Lake Storage data to Google BigQuery. To add a replication destination, navigate to the Connections tab.

  1. Click Add Connection.
  2. Select the Destinations tab and locate the Google BigQuery connector.
  3. Click the Configure Connection icon at the end of that row to open the New Connection page. If the Configure Connection icon is not available, click the Download Connector icon to install the Google BigQuery connector. For more information about installing new connectors, see Connections in the Help documentation.
  4. After the connected is added, enter the necessary connection properties. To connect to Google BigQuery, use OAuth authentication::
    • Connection Name: Enter a connection name of your choice.
    • Auth Scheme: Select OAuth. Sync supports the OAuth, OAuthJWT, GCPInstanceAccount, and AWSWorkloadIdentity authentication methods.
    • ProjectId: Enter the ID of the project you want to connect to.
    • DatasetId: Enter the ID of the dataset you want to connect to.
    • Insert Mode: Set it to Upload. The different Insert Modes available in Sync are Streaming, DML, Upload, and GCSStaging.
  5. Click Connect to Google BigQuery. Log in using your Gmail credentials to grant permissions to CData Sync. CData Sync completes the OAuth process and connects successfully to Google BigQuery.
  6. Once connected, click Save & Test to save the connection.

You are now connected to Google BigQuery and can use it as both a source and a destination.

NOTE: You can use the Label feature to add a label for a source or a destination.

In this article, we will demonstrate how to load Azure Data Lake Storage data into Google BigQuery and utilize it as a destination.

Configure the Azure Data Lake Storage Connection

You can configure a connection to Azure Data Lake Storage from the Connections tab. To add a connection to your Azure Data Lake Storage account, navigate to the Connections tab.

  1. Click Add Connection.
  2. Select a source (Azure Data Lake Storage).
  3. Configure the connection properties.

    Authenticating to a Gen 1 DataLakeStore Account

    Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.

    For this, an Active Directory web application is required. You can create one as follows:

    1. Sign in to your Azure Account through the .
    2. Select "Entra ID" (formerly Azure AD).
    3. Select "App registrations".
    4. Select "New application registration".
    5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
    6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
    7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

    To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen1.
    • Account: Set this to the name of the account.
    • OAuthClientId: Set this to the application Id of the app you created.
    • OAuthClientSecret: Set this to the key generated for the app you created.
    • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

    Authenticating to a Gen 2 DataLakeStore Account

    To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen2.
    • Account: Set this to the name of the account.
    • FileSystem: Set this to the file system which will be used for this account.
    • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
  4. Click Connect to Azure Data Lake Storage to ensure that the connection is configured properly.
  5. Click Save & Test to save the changes.

Configure Replication Queries

CData Sync enables you to control replication with a point-and-click interface and with SQL queries. For each replication you wish to configure, navigate to the Jobs tab and click Add Job. Select the Source and Destination for your replication.

Replicate Entire Tables

To replicate an entire table, navigate to the Task tab in the Job, click Add Tasks, choose the table(s) from the list of Azure Data Lake Storage tables you wish to replicate into Google BigQuery, and click Add Tasks again.

Customize Your Replication

You can use the Columns and Query tabs of a task to customize your replication. The Columns tab allows you to specify which columns to replicate, rename the columns at the destination, and even perform operations on the source data before replicating. The Query tab allows you to add filters, grouping, and sorting to the replication with the help of SQL queries.

Schedule Your Replication

Select the Overview tab in the Job, and click Configure under Schedule. You can schedule a job to run automatically by configuring it to run at specified intervals, ranging from once every 10 minutes to once every month.

Once you have configured the replication job, click Save Changes. You can configure any number of jobs to manage the replication of your Azure Data Lake Storage data to Google BigQuery.

Run the Replication Job

Once all the required configurations are made for the job, select the Azure Data Lake Storage table you wish to replicate and click Run. After the replication completes successfully, a notification appears, showing the time taken to run the job and the number of rows replicated.

Free Trial & More Information

Now that you have seen how to replicate Azure Data Lake Storage data into Google BigQuery, visit our CData Sync page to explore more about CData Sync and download a free 30-day trial. Start consolidating your enterprise data today!

As always, our world-class Support Team is ready to answer any questions you may have.

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