About Weaviate
Weaviate is an open source vector database for search and AI applications. It stores data as vectors so applications can find items by meaning, not only by exact keywords.
What it does
Weaviate stores, indexes and searches high-dimensional vectors. It can also create embeddings from text, images and other data inside the database, so you do not need a separate embedding pipeline. A Query Agent lets users ask questions in plain language, and the system turns those questions into database queries. The database is deployment-agnostic, so it can run in your own environment or as a managed service.
Key features
- Store and search vectors at scale
- Built-in embeddings from text and images
- Natural language questions through Query Agent
- Tenant support for many isolated groups in one cluster
- Run in your own environment or as a managed service
Who it's for
The database suits backend teams, search engineers and developers building retrieval augmented generation or agent systems. Small projects with little data may not need a dedicated vector database.
Pricing and good to know
The core database is open source and free to self-host. The vendor also sells managed cloud and enterprise options, which are priced separately. Running a large cluster needs memory and storage planning, and the costs depend on how much data you keep.
Highlights
- Store and search vectors at scale
- Built-in embeddings from text and images
- Natural language questions through Query Agent
- Tenant support for many isolated groups in one cluster
- Run in your own environment or as a managed service
