alibaba/zvec

Health v2 · maintenance only

Adoption not part of the score

15518 stars · 980 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Zvec is an open-source, in-process vector database by Alibaba that embeds directly into applications with no server or daemon required. It provides fast dense and sparse vector similarity search with hybrid filtering, durable WAL-backed storage, and Python/Node.js SDKs.

Use cases

• run a local vector database without a server
• build semantic search over my documents
• store embeddings for a RAG pipeline
• add similarity search to an existing application
• give AI agents long-term memory with vector search
• search billions of vectors with low latency
• replace faiss with a persistent embedded vector store
• hybrid search combining vectors and metadata filters

When to choose

• you want an embedded, zero-config vector database like SQLite but for vectors
• you need sub-millisecond similarity search at local or billion scale
• you're building RAG, semantic search, or agent memory in Python or Node.js
• you need durable storage with WAL and multi-process reads

When to avoid

• you need a distributed, multi-writer vector database cluster
• your stack requires a language without an official SDK
• you need full-text search as the primary workload rather than vectors

Facets

library · maturity active

vector-database search-engine rag database databases machine-learning artificial-intelligence developer-tools python cpp windows cross-platform self-hosted in-process embedded-database hnsw diskann similarity-search semantic-search llm-memory faiss-alternative local-first sparse-vectors hybrid-search agent-skills mcp-server search retrieval-augmented-generation nodejs linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="alibaba/zvec")