[kolar]

Also Postgres is too slow for large analytical databases. You need columnar database to make fast queries on >1Tb of data.

[martintietz]

As 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

[ttfkam]

1TB 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.

[ithkuil]

Does anyone have experience with some postgres columnar store extension like https://github.com/citusdata/cstore_fdw ?

[whoopdeepoo]

My experience was not enough support for common postgres features

[martintietz]

Agree. Here is a list of the limitations: https://github.com/citusdata/citus/tree/main/src/backend/col...

[ttfkam]

AWS Redshift works wonderfully in that capacity.

[bfelbo]

You could use TimescaleDB which is a Postgres extension that adds support for columnar tables and time-based chunking. Works brilliantly IMO.