zvec
alibaba/zvec
Zvec is a lightweight, in-process vector database optimized for low-latency and scalable similarity search.
Overview
A high-performance vector database embedded within applications, enabling efficient similarity searches with minimal setup. Supports full-text search among other advanced features.
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Install
git clone https://github.com/alibaba/zvecREADME
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Zvec is an open-source, in-process vector database — lightweight, lightning-fast, and designed to embed directly into applications. Battle-tested within Alibaba Group, it delivers production-grade, low-latency and scalable similarity search with minimal setup.
[!Important] 🚀 v0.5.0 (June 12, 2026)
- Full-Text Search (FTS): Native full-text search — attach an FTS index to any string field and query it with natural-language or structured expressions, no external search engine required.
- Hybrid Retrieval: Combine full-text and vector search in a single
MultiQueryacross dense vectors, sparse vectors, scalar filters, and text.- DiskANN Index: New on-disk index that keeps the bulk of the index on disk, drastically cutting memory usage for large-scale datasets.
- Ecosystem & Platforms: New official Go / Rust SDKs, the Zvec Studio visual tool, and RISC-V support.
💫 Features
- Blazing Fast: Searches billions of vectors in milliseconds.
- Simple, Just Works: Install and start searching in seconds. Pure local, no servers, no config, no fuss.
- Dense + Sparse Vectors: Support dense and sparse embeddings, multi-vector queries, and a rich selection of vector index types that scale from memory to disk.
- Full-Text Search (FTS): Native keyword-based full-text search — query string fields with natural-language or structured expressions.
- Hybrid Search: Fuse vector similarity, full-text search, and structured filters in a single query for precise