Qdrant is an open-source vector similarity search engine written in Rust, storing vectors alongside JSON payloads and allowing results to be filtered by those payloads during the search rather than after it. It solves the problem that retrieval usually needs a condition as well as a similarity, such as restricting to one tenant or one document type. It exists because filtering after a vector search silently loses recall: the top matches may all be filtered away. Qdrant can be self-hosted or used as a managed service.
Weaviate is an open-source vector database that combines vector similarity with keyword search in a single query, a technique usually called hybrid search. It solves the problem that pure vector search can miss exact matches: identifiers, error codes and rare terms are poorly represented in embedding space but trivially matched by keywords. It exists because most real corpora need both. It can be self-hosted or consumed as a managed service.