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It was to expect after recent ES releases. However, dedicated vector search engines offer better performance and more advanced features. Qdrant https://github.c
by andre-z 4y ago
It was to expect after recent ES releases. However, dedicated vector search engines offer better performance and more advanced features. Qdrant https://github.com/qdrant/qdrant https://github.com/qdrant/qdrant is written in Rust. Fast, stable, and super easy to deploy. (disclaimer. affiliated with the project).
- jillesvangurp 4y agoI don't think that there's much preventing Elasticsearch or Solr from being as fast. Vector search is expensive. Therefore combining the approach with other filtering and querying makes a lot of sense. It's just another tool for search engineers to use. Probably using vector search exclusively would go at the cost of search quality and performance.
- andre-z 4y agoExactly, filtering is vital. That is why Qdrant offers extended filtering, which happens at the same stage as retrieval, not as pre- or post-filtering, with two stages and an impact on performance and quality. It is not trivial to implement vector search functionality inside a complex framework that is not initially designed for vectors. Besides that, vector search is not only about semantic search.