Earlier quoted context omitted.
Yes, it's great. Part of the issue is that PostgreSQL isn't great at parallelism yet so optimizing the storage greatly reduces compute time to begin with. Unfortunately that extension has a bunch of limitations and issues that keep it from being production-ready. PostgreSQL could really use a proper columnstore table implementation, and there's a pluggable storage API on the roadmap but it hasn't gotten much traction…
And it's... really not all that fast when compared to mature analytical databases. ClickHouse on identical hardware is ~ 100x faster than cstore_fdw. http://tech.marksblogg.com/benchmarks.html More interesting to me is the reverse: using FDW from the analytical DB to Postgres, e.g., https://aws.amazon.com/blogs/big-data/join-amazon-redshift-a...
For the specific dataset I needed to take advantage of some of the additional datatypes that PG has available, which is how I found it.