I've been using ClickHouse too and it's significantly faster than Postgres for certain analytical workloads. I benchmarked it and while Postgres took 47 seconds, ClickHouse finished within 700ms when performing a query on the OpenFoodFacts dataset (~9GB). Interestingly enough TimescaleDB (Postgres extension) took 6 seconds.

^All^ ^actions^ ^were^ ^performed^ ^through^ ^Datagrip^

^1^ ^Insertion^ ^speed^ ^is^ ^influenced^ ^by^ ^reduced^ ^networking^ ^overhead^ ^due^ ^to^ ^the^ ^databases^ ^being^ ^in-process.^

Updates and deletes don't work as well and not being able to perform an upsert can be quite annoying. However, I found the ReplacingMergeTree and AggregatingMergeTree table engines to be good replacements so far.

Also there's !clickhouse@programming.dev