{"id":"weaviate-api","name":"Weaviate","homepage":"https://weaviate.io","repo_url":"https://github.com/weaviate/weaviate","category":"vector-database","subcategories":["vector-search","ai-infrastructure","semantic-search","rag","open-source"],"tags":["weaviate","vector-database","embeddings","semantic-search","rag","graphql","open-source","ai","grpc","hybrid-search"],"what_it_does":"Open-source vector database with built-in vectorization modules, hybrid search (BM25 + vector), and a GraphQL/REST/gRPC API for building semantic search and RAG applications.","use_cases":["RAG pipelines with built-in embedding generation via module integrations (OpenAI, Cohere, etc.)","Hybrid search combining keyword BM25 and semantic vector search","Multi-modal search over text, images, and audio in a single index","Knowledge graph construction with object cross-references","Semantic document retrieval with fine-grained filtering"],"not_for":["Simple key-value lookups or relational queries","Teams who want fully managed infrastructure without any DevOps overhead (self-hosted Weaviate requires operational effort)","Workloads requiring exact keyword matching only"],"best_when":"You want an open-source vector database with powerful hybrid search, built-in vectorization, and the option to self-host or use managed cloud.","avoid_when":"You need a zero-ops managed vector store with minimal configuration or are already invested in a Pinecone/Qdrant ecosystem.","alternatives":["pinecone-api","qdrant-api","chroma-api","elasticsearch-api"],"af_score":79.4,"security_score":null,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"current","last_evaluated":"2026-03-01T09:50:06.397368+00:00","performance":{"latency_p50_ms":15,"latency_p99_ms":100,"uptime_sla_percent":99.9,"rate_limits":"No hard rate limits on self-hosted; WCS limits vary by plan","data_source":"llm_estimated","measured_on":null}}