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Also Postgres is too slow for large analytical databases. You need columnar database to make fast queries on >1Tb of data.
by kolar 4y ago
Also Postgres is too slow for large analytical databases. You need columnar database to make fast queries on >1Tb of data.
- bfelbo 4y agoYou could use TimescaleDB which is a Postgres extension that adds support for columnar tables and time-based chunking. Works brilliantly IMO.
- ithkuil 4y agoDoes anyone have experience with some postgres columnar store extension like https://github.com/citusdata/cstore_fdw https://github.com/citusdata/cstore_fdw ?
- ttfkam 4y agoAWS Redshift works wonderfully in that capacity.
- whoopdeepoo 4y agoMy experience was not enough support for common postgres features
- martintietz 4y agoAgree. Here is a list of the limitations: https://github.com/citusdata/citus/tree/main/src/backend/columnar#limitations https://github.com/citusdata/citus/tree/main/src/backend/col...
- martintietz 4y agoAs always: it depends. For some workloads something like Citus [1] might allow you stay within the PostgreSQL ecosystem even when you are trying to do OLAP. [1] https://github.com/citusdata/citus https://github.com/citusdata/citus
- ttfkam 4y ago1TB is peanuts. You can usually get by even with a lot more. Once that's expired though, you can just switch relatively easily to a different flavor of Postgres. It's why AWS Redshift exists: Postgres with column-oriented storage.