Do AI agents pick Weaviate?
How often agents choose Weaviate when a developer needs vector database — measured across Claude, GPT, Gemini.
95% CI 0%–2%
When developers ask an AI agent for vector db, Weaviate is picked 0% of the time — ranking #4 of 5 measured across Claude, GPT, Gemini.
0 docs in FineWeb · 214 URLs in Common Crawl
1.4M installs / month ▼ 5% MoM
Get the full report
The per-model and per-surface breakdown for Weaviate — where it wins, where it loses, and to whom — plus an alert when the Pick Rate moves.
About Weaviate
An open-source vector database built for storing and querying AI-generated embeddings.
Weaviate is a vector database that lets developers store objects alongside their vector embeddings and perform similarity searches at scale. It is designed for applications that work with machine learning models, such as semantic search, recommendation systems, and retrieval-augmented generation (RAG) pipelines. Developers can run it self-hosted or use a managed cloud version.
Where to start
Start with the general Weaviate documentation to set up an instance, then use the official JS/TS client to connect your application and interact with collections and queries.