How to load data from Kafka to Kafka

Learn how to use Airbyte to synchronize your Kafka data into Kafka within minutes.

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Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.
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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Kafka connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Kafka for your extracted Kafka data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Kafka to Kafka in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
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Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

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How to Sync to Manually

Step 1: Prepare Both Kafka Clusters

Ensure that both Kafka clusters (the source and the destination) are up and running. Verify that each cluster has the necessary topics created. You may need to create topics in the destination cluster that mirror those in the source cluster. This can typically be done using the `kafka-topics.sh` script.

Create a Kafka consumer on the source cluster that subscribes to the topic(s) you want to replicate. This consumer will read data from the source cluster. Use the `kafka-console-consumer.sh` script to test your setup. Customize your consumer using the necessary configuration parameters like `bootstrap.servers`, `group.id`, and `auto.offset.reset`.

Implement logic within your consumer application to process and transform records if needed. This can be done using a custom application written in Java, Python, or any supported Kafka client language. The goal is to prepare the records for publishing to the destination cluster.

Create a Kafka producer that will send the processed records to the destination Kafka cluster. Use the `kafka-console-producer.sh` script to ensure you can connect to the destination cluster initially. Customize your producer with configuration parameters such as `bootstrap.servers` and `acks` to guarantee message delivery.

Integrate the consumer and producer logic within your application. This bridge will read records from the source cluster, process them if necessary, and then publish them to the destination cluster. Ensure that you handle exceptions and retries to maintain reliable data transfer.

Since you are not using any third-party tools, you need to manually manage consumer offsets. Ensure that your application correctly commits offsets after records are successfully produced to the destination cluster. This can be done programmatically through the Kafka consumer API.

Once the application is verified and running correctly, automate the deployment and execution of your application. Use cron jobs, systemd services, or any other scheduling tool to ensure the process runs continuously or at scheduled intervals. Monitor the process logs and Kafka metrics to ensure ongoing data movement without issues.
By following these steps, you will have effectively moved data from one Kafka cluster to another using native Kafka clients and your custom application logic.