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Imagine that you want to join two tables, and filter by a column that comes from the table in the right side of the join. On ClickHouse the query a bit different than what you’d do in other databases like Postgres, and it will result in a big performance improvement.
Let’s say one of the tables is this events table, with 100M rows:
And the other table is this products one, with ~2M rows
If you will always filter the result after making the join as in the query above, you don’t need to make a join at all. ClickHouse saves data column-by-column, so filtering by the values in a column is a very fast operation. If you rewrite the query as follows, it would be just as fast. And you wouldn’t have create a Join table for it:
Tinybird lets you create real-time API endpoints on in minutes instead of hours of days, powered by ClickHouse. We’re still in private beta, but if you want to try out product, create an account here.
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