I'm not fully familiar with Hydra. From my understanding, they forked Citus columnar and improved it. I think the use case for just pg_analytics vs hydra is similar, i.e. fast analytics in Postgres. However, soon they'll diverge as we interoperate it with pg_bm25, our full-text search extension. We see ParadeDB as becoming a modern alternative to Elasticsearch, while Hydra appears to be positioning itself as a Postgres warehouse

In philosophy, we believe in playing into the ecosystem. We use DataFusion to avoid needing to write a vectorized query engine, Arrow to avoid needing to build an in-memory representation, and Parquet to avoid needing to build columnar disk storage. Citus columnar/Hydra appear to be working from first principles directly within Postgres, storing data in Postgres blocks, and writing vectorized execution operator by operator