Overview
Zvec is an open-source, fast, lightweight, and feature-rich vector database that runs entirely in-process — no server, daemon, or external infrastructure required. Just install the package and start indexing and querying vectors right away 🚀.
Vector databases are commonly used to power AI applications like semantic search, retrieval-augmented generation (RAG), recommendation systems, and other similarity-based workflows.
Zvec can serve as a standalone vector database for end-to-end storage and search, or it can be seamlessly integrated into existing search systems (such as traditional SQL databases) as a dedicated vector search engine.
Battle-tested across demanding production workloads within Alibaba Group, Zvec delivers production-grade, low-latency and scalable similarity search. With its minimal-dependency, in-process design, Zvec is well-suited for virtually any scenario:
- 💻 From rapid prototyping and local development
- 📱 To embedded applications and edge deployments
- 🌐 All the way to billion-scale, production-grade systems
Key Features
- ⚡ Blazing Fast: Scale to billions of vectors with sub-millisecond search latency.
- 🧩 Simple, Just Works: A single package is all you need — install it and start searching in seconds. No servers, no config, no fuss.
- ✨ Dense + Sparse Vectors: Work with both dense and sparse embeddings, with native support for multi-vector queries in a single call.
- 🎯 Hybrid Search: Combine semantic similarity with structured filters for precise results.
- 🛡️ Durable Storage: Write-ahead logging (WAL) guarantees persistence — data is never lost, even on process crash or power failure.
- 🔒 Concurrent Access: Multiple processes can read the same collection simultaneously; writes are single-process exclusive.
- 📦 Runs Anywhere: As an in-process library, Zvec runs wherever your code runs — notebooks, servers, CLI tools, or even edge devices.