An in-memory Vector Database & AI Gateway written in Go. Supports HNSW, Hybrid Search (BM25), GraphRAG context, a built-in RAG Pipeline, and can be embedded directly into your apps.

ai data-structures database embeddings-similarity go golang hnsw in-memory-database key-value key-value-store knowledge-graph machine-learning no-sql open-source rag rag-pipeline vector-database vector-search
2 Open Issues Need Help Last updated: Jan 2, 2026

Open Issues Need Help

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AI Summary: This issue proposes adding a new lightweight `/healthz` HTTP endpoint to KektorDB. Its purpose is to provide a standard way for Docker health checks and monitoring systems to verify the service's liveness without triggering heavy operations. The endpoint should return HTTP 200 OK with a `{"status": "ok"}` JSON body and ideally bypass any authentication middleware.

Complexity: 1/5
good first issue

An in-memory Vector Database & AI Gateway written in Go. Supports HNSW, Hybrid Search (BM25), GraphRAG context, a built-in RAG Pipeline, and can be embedded directly into your apps.

Go
#ai#data-structures#database#embeddings-similarity#go#golang#hnsw#in-memory-database#key-value#key-value-store#knowledge-graph#machine-learning#no-sql#open-source#rag#rag-pipeline#vector-database#vector-search
enhancement help wanted good first issue

An in-memory Vector Database & AI Gateway written in Go. Supports HNSW, Hybrid Search (BM25), GraphRAG context, a built-in RAG Pipeline, and can be embedded directly into your apps.

Go
#ai#data-structures#database#embeddings-similarity#go#golang#hnsw#in-memory-database#key-value#key-value-store#knowledge-graph#machine-learning#no-sql#open-source#rag#rag-pipeline#vector-database#vector-search