[mritchie712]

> Recently, the most interesting rift in the Postgres vs OLAP space is [Hydra](https://www.hydra.so), an open-source, column-oriented distribution of Postgres that was very recently launched (after our migration to ClickHouse). Had Hydra been available during our decision-making time period, we might’ve made a different choice.

There will likely be a good OLAP solution (possibly implemented as an extension) in Postgres in the next year or so. There are a few companies are working on it (Hydra, Parade[0], tembo etc.).

0 - https://www.paradedb.com/

[riku_iki]

> 0 - https://www.paradedb.com/

this looks like repackaging of datafusion as PG extension?..

[mritchie712]

yes, that's a succinct way to put it.

[snihalani]

Have you seen: https://benchmark.clickhouse.com/

[iimblack]

That’s cool. Clickhouse and Alloy’s performances are impressive.

[riku_iki]

that benchmark is very weak, they used just 100M rows which is laughable, also no joins have been tested.

[mritchie712]

no joins is heavily favoring clickhouse (the creator of the benchmark). I'm not sure it's gotten better since I've seriously looked at them, but CH's join performance was really bad.

[philippemnoel]

ParadeDB founder here. You can see how we compare to other Postgres-based analytical offerings on ClickBench here: https://blog.paradedb.com/pages/introducing_analytics

[ddorian43]

I don't think `tembo` is working on it though, probably just hosting an existing extension.

[Mortiffer]

so Paradedb and Hydra are using same codebase or just similar approach ?

[philippemnoel]

ParadeDB and Hydra are completely different. We're tackling the same problem of bringing analytics inside Postgres, but using different approaches.

ParadeDB integrates industry standards like Arrow, Parquet, DataFusion to offer columnar storage + vectorized processing. Hydra is building on top of Citus Columnar.

You can read about our approach here: https://blog.paradedb.com/pages/introducing_analytics