Vearch

6.0easy start · #18 of 27
in Vector Databases

Free to practise onnot on record
Free trialnot on record
Well documentedyes
Runs where you worknot on record

Runs on api, self-hosted.

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Vearch is ranked #18 of 27 in vector databases on The Geeks Club. It runs on API, Self-hosted.

Compared on vector databases

Deployment: self-hosted
Metadata filtering: Yes
Index types: HNSW, IVFPQ, GPU, IVFFLAT, BINARYIVF, FLAT
SDK languages: Python, Go, Java, Rust

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The record

Product: Vearch is a cloud-native distributed vector database for similarity search of embedding vectors in AI applications.
Hybrid search: It supports vector search combined with scalar filtering.
Scale and reliability: The project describes replication and elastic scale-out as features, and says it can retrieve millions of objects in milliseconds.
API: The Router provides RESTful upsert, delete, search, and query operations.
SDKs: The project lists Python, Go, Java, and Rust client SDKs.
Integrations: The project lists integrations with LangChain, LlamaIndex, LangChainGo, and LangChain4j.
License: Vearch is licensed under the Apache License, Version 2.0.
Community support: The project points users to GitHub Issues, an email discussion group, and a Slack channel for questions and support.
Visual search requirement: The VisualSearch demo requires an image retrieval plugin for object detection and feature extraction.

Where it ranks on The Geeks Club

Best Vector Databases in 2026#18 of 27

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Sources

github.com/vearch/vearch· checked 4 Oct 2026