Automate Kafka Data Replication to Azure Data Lake

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

Configure Azure Data Lake as a Replication Destination

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

1. Click Add Connection.
2. Select Azure Data Lake as a destination.

3. Enter the necessary connection properties. To connect to Azure Data Lake, set the following properties, depending on your version of Azure Data Lake Storage:

   Azure Data Lake Storage Gen1

   • Generation: Must be set to 1.
   • Account: The name of the Azure Data Lake Store account.
   • Path: The path to store the replicated file (the root directory by default).
   • TenantId: The tenant ID.
   • OAuthClientId: The application ID for the Azure Directory web application (see the CData Sync Help for more information).
   • OAuthClientSecret: The key generated for the Azure Directory web application (see the CData Sync Help for more information).

   Azure Data Lake Storage Gen2

   • Generation: Must be set to 2.
   • Access Key: The access key used to authenticate (see the CData Sync Help for more information).
   • Account: The name of the Azure Data Lake Store account.
   • FileSystem: The file systems used for this account.
   • Path: The path to store the replicated file (the root directory by default).
4. Click Test Connection to ensure that the connection is configured properly.
5. Click Save Changes.

Configure the Kafka Connection

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

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

   Set BootstrapServers and the Topic properties to specify the address of your Apache Kafka server, as well as the topic you would like to interact with.

   Authorization Mechanisms

   • SASL Plain: The User and Password properties should be specified. AuthScheme should be set to 'Plain'.
   • SASL SSL: The User and Password properties should be specified. AuthScheme should be set to 'Scram'. UseSSL should be set to true.
   • SSL: The SSLCert and SSLCertPassword properties should be specified. UseSSL should be set to true.
   • Kerberos: The User and Password properties should be specified. AuthScheme should be set to 'Kerberos'.

   You may be required to trust the server certificate. In such cases, specify the TrustStorePath and the TrustStorePassword if necessary.

4. Click Connect to ensure that the connection is configured properly.
5. Click Save 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, click Add Tables in the Tables section, choose the table(s) you wish to replicate, and click Add Selected Tables.

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.

Schedule Your Replication

In the Schedule section, you can schedule a job to run automatically, configuring the job to run after 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 Kafka data to PostgreSQL.