Schema design

All you need to know about ClickHouse® schema design, including materialized view, limitations, lowcardinality, codecs.
ClickHouse® row-level deduplication

ClickHouse® row-level deduplication.

Column backfilling with alter/update using a dictionary

Functions to count uniqs

Functions to count uniqs.

How much is too much?

ClickHouse® Limitations

How to change ORDER BY

How to change ORDER BY.

Ingestion of AggregateFunction

ClickHouse® - How to insert AggregateFunction data

Insert Deduplication / Insert idempotency

Insert Deduplication / Insert idempotency , insert_deduplicate setting.

JSONEachRow, Tuples, Maps and Materialized Views

How to use Tuple() and Map() with nested JSON messages in MVs

Pre-Aggregation approaches

ETL vs Materialized Views vs Projections in ClickHouse®

Two columns indexing

How to create ORDER BY suitable for filtering over two different columns in two different queries

Best schema for storing many metrics registered from the single source

Codecs

Dictionaries vs LowCardinality

Flattened table

Floats vs Decimals

Ingestion performance and formats

IPs/masks

JSONAsString and Mat. View as JSON parser

LowCardinality

MATERIALIZED VIEWS