Elasticsearch's vector database
Supabase Vector
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 |
Supabase Vector
| Launched | 2017-09 |
| Pricing Model | Free |
| Starting Price | |
| Tech used | Next.js,Vercel,Progressive Web App,RSS,Webpack,HSTS |
| Tag | Vector Database |
Elasticsearch's vector database Rank/Visit
| Global Rank | 29863 |
| Country | United States |
| Month Visit | 1706536 |
Top 5 Countries
Traffic Sources
Supabase Vector Rank/Visit
| Global Rank | 2384 |
| Country | United States |
| Month Visit | 14491339 |
Top 5 Countries
Traffic Sources
Estimated traffic data from Similarweb
What are some alternatives?
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.
Pgvecto.rs - 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.