charabia VS postgres-elasticsearch-fd

I hope to use this to submit a PR to meilisearch/charabia in the future based on the excellent example by benny-n in his pull request adding Hebrew support.

Good to know. If you find some Russian language support improvement we can do, don't hesitate to create an issue on our tokeniser https://github.com/meilisearch/charabia.

Moreover, it's Hacktoberfest. If you want to help us improve the language support, it would be awesome!

The Language support is mainly handled by the tokenizer where you can find specialized Segmenters and Normalizers that target some Language subtilities: https://github.com/meilisearch/charabia

Hi @tommoor

I work at Meilisearch so maybe a biased answer.

We do support other languages than English, it actually depends on what are the languages supported by our tokenizer https://github.com/meilisearch/charabia, so any language that uses whitespace to separate words(including English), Chinese, Japanese, Hebrew and Thai (Japaneze and Thai might work a little bit less)

Hello u/pkeep-go, at MeiliSearch we are implementing with the help of a contributor the CJK language support. We already have the Chinese support with Jieba but a contributor is adding the Korean and Japaneese support with Lindera. For us, it's really important to have people trying and helping us with languages we don't speak. If you want to make any contribution on the tokenization/language support part, we'll be happy to help!

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...