Vearch VS Weaviate

Let’s have a side-by-side comparison of Vearch vs Weaviate to find out which one is better. This software comparison between Vearch and Weaviate is based on genuine user reviews. Compare software prices, features, support, ease of use, and user reviews to make the best choice between these, and decide whether Vearch or Weaviate fits your business.

Vearch

Vearch
Vearch: Hybrid vector search database. Combine similarity & scalar filters for precise AI results. Scale effortlessly. Python/Go SDKs.

Weaviate

Weaviate
Weaviate: The open source vector database powering AI apps. Fast vector search with structured filters. Flexible, scalable, production-ready for developers.

Vearch

Launched
Pricing Model Free
Starting Price
Tech used
Tag Data Science,Semantic Search,Vector Database

Weaviate

Launched 2022-01
Pricing Model Freemium
Starting Price $ 25 /mo
Tech used Google Analytics,Google Tag Manager,Plausible Analytics,Font Awesome,Netlify,KaTeX,Atom,RSS,HSTS
Tag Vector Database

Vearch Rank/Visit

Global Rank
Country
Month Visit

Top 5 Countries

Traffic Sources

Weaviate Rank/Visit

Global Rank 140033
Country India
Month Visit 365919

Top 5 Countries

12.56%
11.74%
6.59%
4.81%
3.58%
India United States Germany China Netherlands

Traffic Sources

4.19%
0.73%
0.1%
8.96%
48.61%
37.17%
social paidReferrals mail referrals search direct

Estimated traffic data from Similarweb

What are some alternatives?

When comparing Vearch and Weaviate, you can also consider the following products

Vector database for Relevance AI - Use managed or self-hosted vector databases to give LLMs the ability to work on YOUR data & context.

Elasticsearch's vector database - Build vector search and hybrid search with Elasticsearch's open source vector database — from the leaders in BM25 text search. Try Elasticsearch's vector database, free....

VectorDB - VectorDB is a simple, lightweight, fully local, end-to-end solution for using embeddings-based text retrieval.

VectorChord - VectorChord is a high-performance PostgreSQL extension for vector similarity search. Enhanced speed, scalability & affordability. Ideal for e-commerce, research & media.

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