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CData Connect Server

Integrate Kafka Data into Automated Tasks with Power Automate



Use CData Connect Server to create a virtual SQL Server database for Kafka data and integrate live Kafka data into your Power Automate (Microsoft Flow) tasks.

Power Automate (Microsoft Flow) is an online service that automates events (known as workflows) across the most common apps and services. When paired with CData Connect Server, you get instant, cloud-to-cloud access to Kafka data for visualizations, dashboards, and more. This article shows how to connect to Connect Server from Power Automate and integrate live Kafka data into your workflows and tasks.

CData Connect Server provides a pure SQL interface for Kafka, allowing you to easily integrate with live Kafka data in Power Automate — without replicating the data. CData Connect Server looks exactly like a SQL Server database to Power Automate and uses optimized data processing out of the box to push all supported SQL operations (filters, JOINs, etc) directly to Kafka, leveraging server-side processing to quickly return Kafka data.

Create a Virtual SQL Database for Kafka Data

CData Connect Server uses a straightforward, point-and-click interface to connect to data sources and generate APIs.

  1. Login to Connect Server and click Connections.
  2. Select "Kafka" from Available Data Sources.
  3. Enter the necessary authentication properties to connect to Kafka.

    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 Save Changes
  5. Click Privileges -> Add and add the new user (or an existing user) with the appropriate permissions.

Connecting to CData Connect Server

To use Connect Server to integrate Kafka data into your Power Automate tasks, you need a new SQL Server connection:

  1. Log in to Power Automate
  2. Click Data -> Connections -> New connection
  3. Select SQL Server
  4. In the connection wizard:

    • Set Authentication Type to "SQL Server Authentication"
    • Set SQL server name to the address of your Connect Server instance (connect_server_url)
    • Set SQL database name to the name of the virtual Kafka database you created earlier (like kafkadb)
    • Set the Username and Password and click Create

Integrating Kafka Data into Power Automate Tasks

With the connection to Connect Server configured, you are ready to integrate live Kafka data into your Power Automate tasks.

  1. Log in to Power Automate
  2. Click My flows -> New and choose to create the flow from blank or template
  3. Add (or configure) a SQL Server action (like Get rows) and configure the action to connect to your Connect Server connection
  4. Select a Table to work with (from the drop-down menu) and configure any advanced options (like filters, orders, etc)
  5. Configure any actions to follow and test, then save the flow

SQL Access to Kafka Data from Applications

Now you have a direct connection to live Kafka data from Power Automate tasks. You can create more connections and workflows to drive business — all without replicating Kafka data.

To get SQL data access to 200+ SaaS, Big Data, and NoSQL sources directly from your applications, see the CData Connect Server.

Related Power Automate Articles

This article walks through using CData Connect Server with Power Automate (Online). Check out our other articles for more ways to work with Power Automate Desktop: