Automated Continuous Zuora Replication to Google BigQuery

Always-on applications rely on automatic failover capabilities and real-time data access. CData Sync integrates live Zuora 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 Zuora 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 Zuora data into Google BigQuery and utilize it as a destination.

Configure the Zuora Connection

You can configure a connection to Zuora from the Connections tab. To add a connection to your Zuora account, navigate to the Connections tab.

1. Click Add Connection.
2. Select a source (Zuora).
3. Configure the connection properties.
   
   

   Zuora uses the OAuth standard to authenticate users. See the online Help documentation for a full OAuth authentication guide.

   Configuring Tenant property

   In order to create a valid connection with the provider you need to choose one of the Tenant values (USProduction by default) which matches your account configuration. The following is a list with the available options:

   • USProduction: Requests sent to https://rest.zuora.com.
   • USAPISandbox: Requests sent to https://rest.apisandbox.zuora.com"
   • USPerformanceTest: Requests sent to https://rest.pt1.zuora.com"
   • EUProduction: Requests sent to https://rest.eu.zuora.com"
   • EUSandbox: Requests sent to https://rest.sandbox.eu.zuora.com"

   Selecting a Zuora Service

   Two Zuora services are available: Data Query and AQuA API. By default ZuoraService is set to AQuADataExport.

   DataQuery

   The Data Query feature enables you to export data from your Zuora tenant by performing asynchronous, read-only SQL queries. We recommend to use this service for quick lightweight SQL queries.

   Limitations
   • The maximum number of input records per table after filters have been applied: 1,000,000
   • The maximum number of output records: 100,000
   • The maximum number of simultaneous queries submitted for execution per tenant: 5
   • The maximum number of queued queries submitted for execution after reaching the limitation of simultaneous queries per tenant: 10
   • The maximum processing time for each query in hours: 1
   • The maximum size of memory allocated to each query in GB: 2
   • The maximum number of indices when using Index Join, in other words, the maximum number of records being returned by the left table based on the unique value used in the WHERE clause when using Index Join: 20,000

   AQuADataExport

   AQuA API export is designed to export all the records for all the objects ( tables ). AQuA query jobs have the following limitations:

   Limitations
   • If a query in an AQuA job is executed longer than 8 hours, this job will be killed automatically.
   • The killed AQuA job can be retried three times before returned as failed.
   
4. Click Connect to Zuora 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 Zuora tables you wish to replicate into Google BigQuery, and click Add Tasks again.

Customize Your Replication

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 Zuora data to Google BigQuery.

Run the Replication Job

Once all the required configurations are made for the job, select the Zuora 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 Zuora 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.