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Very happy with our choice to use TimescaleDB. The idea to simply make it a Postgres extension was brilliant. The compression release was one of the cooler features I've seen in recent times. Row database for recent transactional data, columnar compressed database for historical OLAP workloads - pretty much automagically.

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Curious how large a dataset you're using?

Under 100GB; I'm sure vanilla Postgres would suit our needs too. However, adding TimescaleDB on top was not much of an investment and in exchange we got an interface for operations we do often, effortless continuous aggregation, near-constant time appends, and a native way to leave data mutable for a period of time before marking it immutable and compressing it.

The performance is a great feature but its also just an intuitive, familiar (pretty much just SQL) tool that makes life easier.

Cool. I'm keen to try it. Wondering how well it works with multi-terabyte data sets.

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