Elasticsearch's vector database
Clientvectorsearch
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 |
Clientvectorsearch
| Launched | 2023-8 |
| Pricing Model | Free |
| Starting Price | |
| Tech used | Next.js,Vercel,Gzip,OpenGraph,Webpack,HSTS |
| Tag | Data Science |
Elasticsearch's vector database Rank/Visit
| Global Rank | 29863 |
| Country | United States |
| Month Visit | 1706536 |
Top 5 Countries
Traffic Sources
Clientvectorsearch Rank/Visit
| Global Rank | 0 |
| Country | |
| Month Visit | 1048 |
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.
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.