Best Practices in ClickHouse

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This section provides the best practices you will want to follow to get the most out of ClickHouse.

Page	Description
Choosing a Primary Key	How to select primary keys that maximize query performance and minimize storage overhead.
Select Data Types	Choose optimal data types to reduce memory usage, improve compression, and accelerate queries.
Use Materialized Views	Leverage materialized views to pre-aggregate data and dramatically speed up analytical queries.
Minimize and Optimize JOINs	Best practices for using ClickHouse’s JOIN capabilities efficiently.
Choosing a Partitioning Key	Select partitioning strategies that enable efficient data pruning and faster query execution.
Selecting an Insert Strategy	Optimize data ingestion throughput and reduce resource consumption with proper insert patterns.
Data Skipping Indices	Apply secondary indices strategically to skip irrelevant data blocks and accelerate filtered queries.
Avoid Mutations	Design schemas and workflows that eliminate costly UPDATE/DELETE operations for better performance.
Avoid OPTIMIZE FINAL	Prevent performance bottlenecks by understanding when OPTIMIZE FINAL hurts more than it helps.
Use JSON where appropriate	Balance flexibility and performance when working with semi-structured JSON data in ClickHouse.