SELECT toStartOfMonth(upload_date) AS month, sum(view_count) AS `Youtube Views`, bar(sum(has_subtitles) / count(), 0.55, 0.7, 100) AS `% Subtitles` FROM youtube WHERE (month >= '2020-08-01') AND (month <= '2021-08-01') GROUP BY month ORDER BY month ASC
13 rows in set. Elapsed: 0.823 sec Processed 1.07 billion rows, 11.75 GB (1.30 billion rows/s., 14.27 GB/s.)
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Speed up queries from any data source
ClickHouse supports all the data sources you need to power your apps and use cases that require exceptional performance.
Why is ClickHouse so fast?
Column-oriented databases are better suited to OLAP scenarios. They are at least 100x faster in processing most queries. ClickHouse uses all available system resources to their full potential to process each analytical query as fast as possible.
Row-oriented databases
In row-oriented databases, data is stored in rows, with all the values related to a row physically stored next to each other.