Vearch
Vearch is a free, open-source distributed vector database for similarity search in AI applications.
What Vearch is
Vearch is a free, open-source distributed vector database for similarity search in AI applications. It searches embedding vectors and supports combining vector search with scalar filtering, so results can be constrained by metadata. The project describes replication and elastic scale-out, and says it can retrieve millions of objects in milliseconds. Its Router offers REST operations for upserting, deleting, searching, and querying data. Client SDKs are listed for Python, Go, Java, and Rust, with integrations for LangChain, LlamaIndex, LangChainGo, and LangChain4j. Deployment choices include Kubernetes with Helm, Docker Compose in standalone or cluster mode, Docker, and compilation from source. Vearch is licensed under Apache License 2.0. Its storage design uses Raft-based replication for document partitions, and Gamma, based on Faiss, is its core vector search engine. The project directs users to GitHub Issues, an email discussion group, and Slack for community support. One database management limit is that a database cannot be deleted while it contains a space. The VisualSearch demo also requires an image retrieval plugin for object detection and feature extraction.
Good
- Combines vector search with scalar filtering.
- Describes replication and elastic scale-out.
- SDKs are listed for four programming languages.
- Offers Kubernetes, Docker, and source deployment options.
- Licensed under Apache License 2.0.
Watch out
- A database cannot be deleted while it contains a space.
- VisualSearch requires an image retrieval plugin.
- The project reports no SECURITY.md policy or published advisories.
Who it suits
Vearch suits teams building AI applications that need vector similarity search with metadata filtering. It is also relevant to teams that want to choose among documented deployment methods and use supported client SDKs or framework integrations.
Verdict
Vearch combines vector search, metadata filtering, and several deployment paths for AI application teams. Note the database deletion restriction and the VisualSearch plugin requirement.
Plans and prices
From Vearch's own pricing page, checked 10 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| Vearch | Free | Apache License, Version 2.0 · self-hosted deployment |
The facts
Each one read from Vearch's own pages, with the date it was checked.
What it does
- API
- The Router exposes REST endpoints for upsert, delete, search, and query operations.checked 10 Oct 2026
- Community support
- The project points users to GitHub Issues, an email discussion group, and a Slack channel for questions and support.checked 4 Oct 2026
- Deployment
- Documented deployment options include Kubernetes with Helm, Docker Compose, Docker, and source compilation.checked 10 Oct 2026
- Framework integrations
- The README lists LangChain, LlamaIndex, Langchaingo, and LangChain4j integrations.checked 10 Oct 2026
- Hybrid search
- It supports vector search together with scalar filtering.checked 10 Oct 2026
- Integrations
- The project lists integrations with LangChain, LlamaIndex, LangChainGo, and LangChain4j.checked 4 Oct 2026
- License
- Vearch is licensed under Apache License, Version 2.0.checked 10 Oct 2026
- Notable limit
- The Vearch 3.5 database guide says a database cannot be deleted while it contains a space.checked 10 Oct 2026
- Product
- Vearch is a cloud-native distributed vector database for similarity search of embedding vectors in AI applications.checked 10 Oct 2026
- Scale and reliability
- The project describes replication and elastic scale-out as features.checked 10 Oct 2026
- SDKs
- The README lists Python, Go, Java, and Rust SDKs.checked 10 Oct 2026
- Search performance
- The project says it can retrieve vectors among millions of objects in milliseconds.checked 10 Oct 2026
- Security policy
- GitHub's security page says the repository has no SECURITY.md policy and no published security advisories.checked 10 Oct 2026
- Storage engine
- PartitionServer hosts document partitions with Raft-based replication, and Gamma is the core vector search engine based on Faiss.checked 10 Oct 2026
- Support
- The project directs users to GitHub Issues, a public email discussion list, and Slack for community support.checked 10 Oct 2026
- Supported build environments
- Vearch's installation guide says CentOS, Ubuntu, and Mac OS are supported for compiling the software.checked 10 Oct 2026
- Visual search requirement
- The VisualSearch demo requires an image retrieval plugin for object detection and feature extraction.checked 4 Oct 2026
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