Data modelling overview

Overview of Data Modelling

This section is about data modeling in ClickHouse and contains the following topics:

Page	Description
Schema Design	Discusses ClickHouse schema design for optimal performance, considering factors like queries, data updates, latency, and volume.
Sparse primary indexes	A practical introduction to primary indexes in ClickHouse.
Denormalizing Data	Discusses the denormalization approach used in ClickHouse which aims to improve query performance by storing related data in a single table.
Backfilling Data	Techniques for efficiently backfilling data into ClickHouse tables.
Merge table function	Using the Merge table function to query multiple tables as one.
Stored procedures and prepared statements	Stored procedures and query parameters in ClickHouse.
Generating test data	How to generate random test data in ClickHouse.
Data Compression	Discusses various compression modes in ClickHouse and how to optimize data storage and query performance by choosing the right compression method for your specific data types and workloads.
Working with arrays	Working with arrays in ClickHouse.
Working with JOINs	Working with JOINs in ClickHouse.