postgres-elasticsearch-fd VS PostgreSQL

My experience with Postgres FTS (did a comparison with Elastic a couple years back), is that filtering works fine and is speedy enough, but ranking crumbles when the resulting set is large.

If you have a large-ish data set with lots of similar data (4M addresses and location names was the test case), Postgres FTS just doesn't perform.

There is no index that helps scoring results. You would have to install an extension like RUM index (https://github.com/postgrespro/rum) to improve this, which may or may not be an option (often not if you use managed databases).

If you want a best of both worlds, one could investigate this extensions (again, often not an option for managed databases): https://github.com/matthewfranglen/postgres-elasticsearch-fd...

Either way, writing something that indexes your postgres database into elastic/opensearch is a one time investment that usually pays off in the long run.

I used a foreign data wrapper to query elasticsearch indexes from within postgres.[0]

It pushed alot of complexity down away from higher-level app developers not familiar with ES patterns.

[0]: https://github.com/matthewfranglen/postgres-elasticsearch-fd...

Data Handling: Utilizes Windmill for data pipelines, with a primary database powered by PostgreSQL. Auxiliary data storage is handled by MongoDB, with Redis for caching to optimize performance

PostgreSQL

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Node.js, MySQL and PostgreSQL servers installed on your machine

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