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Kafka to ClickHouse Real-Time Sync | NineData

Use this workflow when Kafka event data needs to land in ClickHouse for dashboards, reports, or other analytical queries. NineData Data Replication can keep the target updated while the source keeps accepting new events.

Overview​

Kafka is good at ingesting events. ClickHouse is better at querying them. Use NineData when you want to move streaming data into an analytical target without building the replication logic yourself.

When to use this workflow​

Use this workflow when you need to:

  • Build near-real-time analytics from streaming events.
  • Offload reporting queries from upstream systems.
  • Keep a ClickHouse target aligned with Kafka messages.
  • Validate replication before downstream teams use the data.

How NineData helps​

  • Add Kafka and ClickHouse as data sources.
  • Configure field mapping when source and target structures differ.
  • Run full and incremental synchronization in one task.
  • Monitor delay, comparison results, and alerts from the task page.

Before you begin​

  • Make sure you can access the NineData console.
  • Prepare the connection information and permissions for the Kafka source and ClickHouse target.
  • Confirm that NineData can reach both systems through the network path you plan to use.
  • Decide how source messages should map to ClickHouse tables and columns.

Procedure​

  1. Add the Kafka data source to NineData.
  2. Add the ClickHouse data source to NineData.
  3. Create a replication task for Kafka and ClickHouse, configure the required objects and mapping, run the precheck, and start the task.

Result​

After the task starts, ClickHouse keeps receiving Kafka changes according to the selected replication scope. Use data comparison and alerts to watch the task during steady-state sync.