ClickHouse, explained in pictures.

Visual guides to how ClickHouse stores, skips, merges and serves data—so you can use it efficiently from day one.

The short answer: it reads less.

One query, three cuts. Partitions, indexes and columns take a 2 TiB table down to about 4.5 MiB.

Large table, small readPausePaused

Illustrative exampleSizes and ratios are typical, not measured; the picture is not to scale.

Columnar storage

Read only the columns you need.

Each column is its own compressed file. The same query opens 4 of them and skips tenant_id and the wide payload: about 38 GiB instead of 5 TiB, before any rows are skipped.

Row layout vs column layoutPausePaused

Illustrative exampleColumns only: sizes are for the whole table before any pruning, so every row of the 4 columns is read and then filtered. The next section shows how the indexes skip most of these rows. Sizes and ratios are typical, not measured.

Primary index · skip index

Sort once. Skip granules before reading.

Two small indexes decide what to read. The same query: the primary index finds the key range, a skip index drops granules whose min/max cannot match. Across the table that leaves 192 of ≈ 1.66 M granules; the 8 below show how.

Sorted data, sparse primary index, skip indexPausePaused

Illustrative example8 neighbouring granules of one part in partition 2025-06-08, the day the 7-day window starts: rows inserted 08:00–12:00, sorted by event_type and timestamp. Across the whole table (≈ 1.66 M granules) the primary index keeps 288 granules and the skip index 192, ≈ 4.5 MiB: the total in the first figure.

Materialized views · table engines

Prepare results at insert time.

Views feed small, pre-aggregated tables. Each insert is summarized once, as it arrives, and the table engine merges the summaries in the background. Dashboards read a few hundred rows instead of billions.

Materialized views and table enginesPausePaused

Illustrative exampleOne insert feeds three views; each table engine merges its rows in the background. Values are illustrative.