pgrx VS tantivy

Consider also the companies and work behind pgrx [0] and pgzx [1]:

[0] https://github.com/pgcentralfoundation/pgrx

[1] https://github.com/xataio/pgzx

If you like this (I do very much), you might also like pg_idkit[0] which is a little extension with a bunch of other kinds of IDs that you can generate inside PG, thanks to the seriously awesome pgrx[1] and Rust.

[0]: https://github.com/VADOSWARE/pg_idkit

[1]: https://github.com/pgcentralfoundation/pgrx

(disclosure, i work at supabase and have been developing TLEs with the RDS team)

Trusted Language Extensions refer to an extension written in any trusted language. In this case Rust, but it also includes: plpgsql, plv8, etc. See [0]

> PL/Rust is a more performant and more feature-rich alternative to PL/pgSQL

This is only partially true. plpgsql has bindings to low-level Postgres APIs, so in some cases it is just as fast (or faster) than Rust.

> Building a vector index (or any index for that matter) inside Postgres is a more involved process and can not be done via the UDF interface, be it Rust, C or PL/pgSQL

Most PG Rust extensions are written with the excellent pgrx framework [1]. While it doesn't have index bindings right now, I can certainly imagine a future where this is possible[2].

All that said - I think there are a lot of hoops to jump through right now and I doubt it's worth it for the Latern team. I think they are right to focus on developing a separate C extension

[0] TLE: https://supabase.com/blog/pg-tle

[1] pgrx: https://github.com/pgcentralfoundation/pgrx

[2] https://github.com/pgcentralfoundation/pgrx/issues/190#issue...

I’m currently playing with PostgreSQL, foreign data wrappers, and pgrx rust extensions. My development experience has been surprisingly smooth and enjoyable.

My main issue is that joins will be processed locally, so all the foreign data will be fetched before the join happens. But otherwise basic CRUD is easy.

https://wiki.postgresql.org/wiki/Foreign_data_wrappers

https://github.com/pgcentralfoundation/pgrx

https://github.com/supabase/wrappers

I think maybe what you’re really looking for are the files here: https://github.com/pgcentralfoundation/pgrx/tree/c2eac033856...

Those are the internals we currently expose as unsafe “sys” bindings.

As we/contributors identify more that are desired we add them.

pgrx’ focus is on providing safe wrappers and general interfaces to the Postgres internals, which is the bulk of our work and is what will take many years.

As unsafe bindings go, we could just expose everything, and likely eventually will. There’s just some practical management concerns around doing that without a better namespace organization —- something we’ve been working.

The Postgres sources are not small. They are very complex, inconsistent in places, and often follow patterns that are specific to Postgres and not easy to generalize.

If you’ve never built an extension with pgrx, give it a shot one afternoon. It’s very exciting to see your own code running in your database.

pgrx is one of the greatest enabling innovations in the PG ecosystem in a long time.

Awesome to see so many high quality extensions come out of it.

https://github.com/pgcentralfoundation/pgrx

If you're interested in what my Threadripper 3970X does with it, there's some numbers in this PR: https://github.com/tcdi/pgrx/pull/1147

Tantivy - a full-text indexing library written in Rust. Has a great performance and featureset.

By this I presume you mean build a search index that can retrieve results based on keywords? I know certain databases use Lucene to build a keyword-based index on top of unstructured blobs of data. Another alternative is to use Tantivy (https://github.com/quickwit-oss/tantivy), a Rust version of Lucene, if building search indices via Java isn't your cup of tea :)

Both libraries offer multilingual support for keywords, I believe, so that's a benefit to vector search where multilingual embedding models are rather expensive.

We also implemented our schemaless columnar storage optimized for object storage.

The inverted index and columnar storage are part of tantivy [0], which is the fastest search library out there. We maintain it and we decided to build the distributed engine on top of it.

[0] tantivy github repo: https://github.com/quickwit-oss/tantivy

The issue for geo search is here: https://github.com/quickwit-oss/tantivy/issues/44

Search index : Custom-built using tantivy.

The roaring bitmap variant is used only for the optional index (1 docid => 0 or 1 value) in the columnar storage (DocValues), not for the inverted index. Since this is used for aggregation, some queries may be a full scan.

The inverted index in tantivy uses bitpacked values of 128 elements with a skip index on top.

> I didn't follow the rest of your comment, select is what EF is good at, every other data structure needs a lot more scanning once you land on the right chunk. With BMI2 you can also use the PDEP instruction to accelerate the final select on a 64-bit block

The select for the sparse codec is a [simple array index access](https://github.com/quickwit-oss/tantivy/blob/main/columnar/s...), that is hard to beat. Compression is not good near the 5k threshold though.

Hi /r/rust, I’m a SWE on Etsy’s Retrieval Systems team where we’re building a platform based on rust and tantivy (https://github.com/quickwit-oss/tantivy). We’re looking to bring two new engineers onto the team.

Quick Search: Easily find specific notes with Velo's fuzzy-search feature, powered by tantivy. tantivy might have been a little overkill, but it was really easy to integrate.