Another reason to use it is that AWS has an OpenSearch service, and afaik it's the only vector store db I can use while keeping my company's legal and security depts happy. (edit: and satisfies my other requirements)
@Logan M I did get a basic boolean filter to work by small edits to llama-index/vector_stores/opensearch.py, but comparing functionality in more depth I think a wrapper is a better option until llama-index implements something more sophisticated.
Yea the vector store integrations are mostly community driven. Feel free to make a PR. Sadly opensearch is barely used (at least judging from discord/github issues), so it's a little barebones at the moment
As it turns out, OpenSearch's KNN filtering is applied after the k-results are retrieved anyway, and as such it would be just about as easy to filter the response instead of asking for a filtered response. Their Lucene engine has pre-filtering, but it only supports up to dimension 1024
tl;dr exact match filtering might not behave as expected unless you are using "Script Scoring" or "Painless Scripting", but those are not as scalable / flexible as the approximate-Knn to which only a "boolean" filter may be applied.