alibaba/zvec
A lightweight, lightning-fast, in-process vector database
This helps developers integrate powerful search capabilities directly into their applications. It takes in collections of "vector embeddings" – numerical representations of text, images, or other data – and allows for lightning-fast similarity searches. The output is a list of relevant results, sorted by how closely they match a query. Developers building AI agents, recommendation systems, or semantic search features would use this.
8,900 stars. Actively maintained with 53 commits in the last 30 days.
Use this if you need to perform extremely fast, low-latency similarity searches on large datasets of vector embeddings directly within your application, without managing a separate server.
Not ideal if you need a standalone database server or a managed service for your vector search, rather than an in-process library.
Stars
8,900
Forks
501
Language
C++
License
Apache-2.0
Category
Last pushed
Mar 13, 2026
Commits (30d)
53
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