Developer Frameworks & Infrastructure
Weaviate
Open-source vector search engine with hybrid search and multimodal indexing
Open sourceRuns in the cloudEditors pick
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Open Source
Free
Platforms
Web
Hosted app
Category
Developer Frameworks & Infrastructure
133 tools
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Last updated
Nov 4
Listing updated
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Enterprise hybrid search systems
Blend dense semantic vectors with sparse BM25 keyword matching for optimal search relevance.
Pricing checked Nov 2026
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About Weaviate
Weaviate is an open-source vector database designed for production-scale generative search. Featuring native support for hybrid search (combining dense vectors with BM25 keyword matching), integrated ML vectorization modules, and GraphQL and gRPC APIs, Weaviate handles billions of objects reliably.
- Native hybrid search combining sparse BM25 and dense vector ranking out of the box
- High-performance gRPC interfaces for millisecond query response times
- Extensive ecosystem of native embedding modules and vectorizers
- More complex operational footprint than lightweight embedded databases
- Requires dedicated RAM allocation for in-memory HNSW index structures
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