Skip to content
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion docs/data-compression/compression-in-clickhouse.md
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@ keywords: ['compression', 'codec', 'encoding']

One of the secrets to ClickHouse query performance is compression.

Less data on disk means less I/O and faster queries and inserts. The overhead of any compression algorithm with respect to CPU will in most cases be out weighted by the reduction in IO. Improving the compression of the data should therefore be the first focus when working on ensuring ClickHouse queries are fast.
Less data on disk means less I/O and faster queries and inserts. The overhead of any compression algorithm with respect to CPU is in most cases outweighed by the reduction in IO. Improving the compression of the data should therefore be the first focus when working on ensuring ClickHouse queries are fast.

> For why ClickHouse compresses data so well, we recommended [this article](https://clickhouse.com/blog/optimize-clickhouse-codecs-compression-schema). In summary, as a column-oriented database, values will be written in column order. If these values are sorted, the same values will be adjacent to each other. Compression algorithms exploit contiguous patterns of data. On top of this, ClickHouse has codecs and granular data types which allow users to tune the compression techniques further.

Expand Down