What is better to use for quick data access: Kafka or ClickHouse?

For quick access to data, especially for analytical queries and aggregation, ClickHouse significantly outperforms Kafka. Kafka is a distributed messaging system optimized for sequential writing and asynchronous processing of large volumes of data, but not for arbitrary reading and analytical queries. ClickHouse, on the other hand, is a columnar analytical database designed specifically for high-speed execution of SELECT queries over massive tables.

Kafka:

• Purpose: Stream data transfer, buffering, system integration.
• Data model: Log of records.
• Access: Sequential reading by offsets.
• SELECT performance: Very low or none for analytical tasks.

ClickHouse:

• Purpose: Data analytics (OLAP), fast SELECT queries.
• Data model: Columnar DBMS.
• Access: Arbitrary reading, optimized for GROUP BY, AGGREGATE, FILTER queries.
• SELECT performance: High to extremely high.

Synergy:

Kafka is often used as a data source for ClickHouse. Data from Kafka is consumed and loaded into ClickHouse, where it becomes available for fast analytical access. For this purpose, special table engines (e.g., Kafka engine in ClickHouse) or separate connectors/ETL processes are used.

Choice:

• If you need fast analytical access and execution of complex SQL queries over large data volumes, choose ClickHouse.
• If you need streaming delivery and buffering of data before processing or analysis, choose Kafka.