If you can model the domain, then you can achieve very good compression.

See this recent timescaledb post (since you mentioned Postgres) which goes over an array of techniques used in column-store databases that general-purpose compressors on a csv file full of data would not be able to match:

https://blog.timescale.com/blog/building-columnar-compressio... discussion: https://news.ycombinator.com/item?id=21412596

I've been happy with influxdb, but I've also noticed that a lot of people switch to a time series database way before they need to. You can go pretty far with postgres/oracle/sql server, and it has the advantage you don't need to manage different databases.

I've never used it myself, but kdb+ is meant to be excellent if you need it.

There's TimescaleDB built on top of PostgreSQL.