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I'm in the same camp. Do you use any specific extensions? Especially for OLAP and time series (partitioned tables + related extensions work fine, but curious if you use anything else)

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The native extensions are fine but I don't have good experience with any third party extensions, so far tried Timescale, pg_lake, citus, and pgvectorscale. They look very appealing but it's usually a trap as you can't get the value without using the vendor's cloud offerings.

I think if you grow enough to look for these extensions, it's usually better to bet on purpose-specific tooling. For example, I use DuckDB/Iceberg combination extensively for columnar data and connect DuckDB to PG when I need it.

Fair enough. How do you do BM25?

From experience, I'd suggest using ClickHouse beyond a few billion rows of timeseries data in Postgres.

Nice thing about our use case is that its not strictly analytics, but looking at most recent raw data. ClickHouse is definitely the powerhouse for analytics

ClickHouse is fine for looking at recent data (with simple / efficient TTL). I'd still (probably) use Postgres for smaller scale things however.

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