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Integrating Kafka with ClickHouse

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. ClickHouse provides multiple options to read from and write to Kafka and other Kafka API-compatible brokers (e.g., Redpanda, Amazon MSK).

Available options​

Choosing the right option for your use case depends on multiple factors, including your ClickHouse deployment type, data flow direction and operational requirements.

OptionDeployment typeFully managedKafka to ClickHouseClickHouse to Kafka
ClickPipes for KafkaCloud, BYOC (coming soon!)✅✅
Kafka Connect SinkCloud, BYOC, Self-hosted✅
Kafka table engineCloud, BYOC, Self-hosted✅✅

For a more detailed comparison between these options, see Choosing an option.

ClickPipes for Kafka​

ClickPipes is a managed integration platform that makes ingesting data from a diverse set of sources as simple as clicking a few buttons. Because it is fully managed and purpose-built for production workloads, ClickPipes significantly lowers infrastructure and operational costs, removing the need for external data streaming and ETL tools.

Tip

This is the recommended option if you're a ClickHouse Cloud user. ClickPipes is fully managed and purpose-built to deliver the best performance in Cloud environments.

Main features​

  • Optimized for ClickHouse Cloud, delivering blazing-fast performance
  • Horizontal and vertical scalability for high-throughput workloads
  • Built-in fault tolerance with configurable replicas and automatic retries
  • Deployment and management via ClickHouse Cloud UI, Open API, or Terraform
  • Enterprise-grade security with support for cloud-native authorization (IAM) and private connectivity (PrivateLink)
  • Supports a wide range of data sources, including Confluent Cloud, Amazon MSK, Redpanda Cloud, and Azure Event Hubs
  • Supports most common serialization formats (JSON, Avro, Protobuf coming soon!)

Getting started​

To get started using ClickPipes for Kafka, see the reference documentation or navigate to the Data Sources tab in the ClickHouse Cloud UI.

Kafka Connect Sink​

Kafka Connect is an open-source framework that works as a centralized data hub for simple data integration between Kafka and other data systems. The ClickHouse Kafka Connect Sink connector provides a scalable and highly-configurable option to read data from Apache Kafka and other Kafka API-compatible brokers.

Tip

This is the recommended option if you prefer high configurability or are already a Kafka Connect user.

Main features​

  • Can be configured to support exactly-once semantics
  • Supports most common serialization formats (JSON, Avro, Protobuf)
  • Tested continuously against ClickHouse Cloud

Getting started​

To get started using the ClickHouse Kafka Connect Sink, see the reference documentation.

Kafka table engine​

The Kafka table engine can be used to read data from and write data to Apache Kafka and other Kafka API-compatible brokers. This option is bundled with open-source ClickHouse and is available across all deployment types.

Tip

This is the recommended option if you're self-hosting ClickHouse and need a low entry barrier option, or if you need to write data to Kafka.

Main features​

  • Can be used for reading and writing data
  • Bundled with open-source ClickHouse
  • Supports most common serialization formats (JSON, Avro, Protobuf)

Getting started​

To get started using the Kafka table engine, see the reference documentation.

Choosing an option​

ProductStrengthsWeaknesses
ClickPipes for Kafka• Scalable architecture for high throughput and low latency
• Built-in monitoring and schema management
• Private networking connections (via PrivateLink)
• Supports SSL/TLS authentication and IAM authorization
• Supports programmatic configuration (Terraform, API endpoints)		• Does not support pushing data to Kafka
• At-least-once semantics
Kafka Connect Sink• Exactly-once semantics
• Allows granular control over data transformation, batching and error handling
• Can be deployed in private networks
• Allows real-time replication from databases not yet supported in ClickPipes via Debezium		• Does not support pushing data to Kafka
• Operationally complex to set up and maintain
• Requires Kafka and Kafka Connect expertise
Kafka table engine• Supports pushing data to Kafka
• Operationally simple to set up		• At-least-once semantics
• Limited horizontal scaling for consumers. Cannot be scaled independently from the ClickHouse server
• Limited error handling and debugging options
• Requires Kafka expertise

Other options​