# Zvec

[Product Introduction] Zvec is an open source, lightweight in-process vector database built on Alibaba's proven Proxima engine. Designed for embedded applications, it provides production-grade, low-latency scalable similarity search capabilities in any code execution environment, from servers to edge devices, without the need for separate server configuration. Zvec aims to help developers quickly build high-performance AI applications such as RAG, image search, and code search through a minimalist architecture. [Product Features] Ultimate performance: Supports millisecond-level retrieval of billions of vectors, and has excellent QPS performance on tens of millions of data sets. Lightweight and easy to use: It adopts the in-process (InProcess) operating mode and is ready to use without complex operation, maintenance and configuration. Hybrid search: supports dense vectors and sparse vectors, and provides hybrid search and group search functions combined with structured filters. Multi-terminal support: Compatible with Python and Node.js, supports Linux and macOS (including ARM64) platforms. Project open source address: https://github.com/alibaba/zvec

[Product Introduction] Zvec is an open source, lightweight in-process vector database built on Alibaba's proven Proxima engine. Designed for embedded applications, it provides production-grade, low-latency scalable similarity search capabilities in any code execution environment, from servers to edge devices, without the need for separate server configuration. Zvec aims to help developers quickly build high-performance AI applications such as RAG, image search, and code search through a minimalist architecture. [Product Features] Ultimate performance: Supports millisecond-level retrieval of billions of vectors, and has excellent QPS performance on tens of millions of data sets. Lightweight and easy to use: It adopts the in-process (InProcess) operating mode and is ready to use without complex operation, maintenance and configuration. Hybrid search: supports dense vectors and sparse vectors, and provides hybrid search and group search functions combined with structured filters. Multi-terminal support: Compatible with Python and Node.js, supports Linux and macOS (including ARM64) platforms. Project open source address: https://github.com/alibaba/zvec

Canonical: https://uniquebase.ai/products/zvec
Stable identifier: UB-D8061
Snapshot captured: 2026-10-28T00:47:51.550Z
English updated: 2026-10-28T00:56:06.702Z

## Connected profiles

- [Zvec](/companies/zvec)

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