Comment by softwaredoug
5 days ago
One thing to _always_ dig into is how your hybrid search solution filters the vector search index. This is not at all standardized, often overlooked, but when you want "top X most similar to query by embedding, but also in Y category/match Z search terms" its the core operation your hybrid search is doing
Here's a rollup of algorithms... https://bsky.app/profile/softwaredoug.bsky.social/post/3lmrm...
Meilisearch is faster when you reduce the dataset by filtering it. I wrote an article on this subject [1].
[1]: https://blog.kerollmops.com/meilisearch-vs-qdrant-tradeoffs-...
"Slowness can arise from a misconfigured index or if filterable attributes aren't listed." ;)