Same. We replicated some data from Postgres, it was easy to set up, similar enough that the transition was trivial, and really good performance out of the box. One of those good "use the right tool for the job" experiences.

How do you use it for visualization? Do you use ClickStack? or something else?

I was using TimescaleDB some very long time ago, things have changed quite a lot since (it's now even named differently).

In my current setup I was thinking on doing both: upgrading postgresql to timescaledb (to archive old data etc.), and to deploy ClickHouse in parallel. I'm still considering whether to go big on PeerDB to get ClickHouse mirror or just deploy it separately without additional fragility layer.

Would you not recommend using timescaledb at all? I definitely want to avoid alpha-quality software pain, since PostgreSQL is one of the most rock-solid parts of the stack at the moment.

Same we are also stuck with ES wish could migrate to clickhouse but not able to do so because of the legacy load.

ClickHouse dev here, but this is true. ClickHouse contributed finding several bugs on our third-party libs (jemalloc, librdkafka for 100%, there much more, but I only worked on these), in linux kernel and basically everywhere. We have very rigorous fuzzers (yes, multiple fuzzers on multiple levels), running tests in insane number of configurations. I think the last number I heard a year ago is around 400 hours for a complete CI run for a single commit (not PR, but commit). So yeah, pretty insane, in the good way.