Irrespective of opensearch, if the dimension of your vector embedding is reasonably large you'll probably want an approximate nearest neighbours approach like H

Irrespective of opensearch, if the dimension of your vector embedding is reasonably large you'll probably want an approximate nearest neighbours approach like HNSW rather than knn itself https://docs.opensearch.org/docs/1.2/search-plugins/knn/approximate-knn/ https://docs.opensearch.org/docs/1.2/search-plugins/knn/appr... For whatever an endorsement from a random stranger is worth, we've been using opensearch for a vectordb for hybrid search across text and multimodal embeddings as well as traditional metadata and it's been great but we're not "full production" yet so I can't really speak to scale, but it's opensearch so I expect the scale to be fine most probably.