Elasticsearch's vector database VS Pgvecto.rs

Let’s have a side-by-side comparison of Elasticsearch's vector database vs Pgvecto.rs to find out which one is better. This software comparison between Elasticsearch's vector database and Pgvecto.rs 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 Elasticsearch's vector database or Pgvecto.rs fits your business.

Elasticsearch's vector database

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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....

Pgvecto.rs

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PGVecto.rs is a Postgres extension that enables scalable vector search, allowing you to build powerful similarity-based applications on top of your Postgres database.

Elasticsearch's vector database

Launched	2010-7
Pricing Model	Freemium
Starting Price
Tech used	Google Analytics,Google Tag Manager,Optimizely,Google Fonts,Next.js,Emotion,Gzip,JSON Schema,OpenGraph,Progressive Web App,Varnish,Webpack,HSTS
Tag	Vector Database,Data Analysis

Pgvecto.rs

Launched
Pricing Model	Freemium
Starting Price
Tech used	Google Analytics,Google Tag Manager,Framer,Google Fonts,Gzip,HTTP/3,OpenGraph,HSTS
Tag	Vector Database,Data Analysis,Sql Assistant

Elasticsearch's vector database Rank/Visit

Global Rank	29863
Country	United States
Month Visit	1706536

Top 5 Countries

19.96%

8.53%

6.12%

4.67%

3.7%

United States China India Korea, Republic of United Kingdom

Traffic Sources

1.77%

0.82%

0.05%

7.31%

51.58%

38.46%

social paidReferrals mail referrals search direct

Pgvecto.rs Rank/Visit

Global Rank	6355648
Country	France
Month Visit	149

Top 5 Countries

100%

France

Traffic Sources

4.66%

1.01%

0.48%

14.26%

43.83%

34.93%

social paidReferrals mail referrals search direct

Estimated traffic data from Similarweb

What are some alternatives?

When comparing Elasticsearch's vector database and Pgvecto.rs, 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.

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

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

clientvectorsearch - Discover the client-vector-search library: embed, store, search, and cache vectors effortlessly. Enhance your applications with efficient vector search capabilities.

More Alternatives

Elasticsearch's vector database VS Vector database for Relevance AI

Elasticsearch's vector database VS VectorDB

Elasticsearch's vector database VS Vearch

Elasticsearch's vector database VS clientvectorsearch