Weaviate
Open-source vector database with hybrid search
- Open source
- Vector Databases
What it is
Weaviate stores objects together with their vectors and can generate the embeddings itself through pluggable vectoriser modules at write time. Dense vector search and keyword BM25 scoring combine into a single hybrid query, exposed over GraphQL and REST against a schema-defined collection model. It runs self-hosted or as a managed cloud service.
Best for
Hybrid semantic and keyword retrieval where you want the database to own embedding generation rather than your pipeline.
Where it falls short
The schema and module system is more to learn than a plain index, and self-hosting means owning memory sizing, upgrades and backups.
Characteristics
- hybrid-search
- graphql
- self-hosted
- vectorisers
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More in Vector Databases
Other tools solving the same problem, so you can see what Weaviate is actually competing with.
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Qdrant
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