- https://github.com/weaviate/weaviate
- https://weaviate.io/
- What is Weaviate?
- Weaviate is an open source vector database that stores both objects and vectors. This allows for combining vector search with structured filtering.
- Weaviate in a nutshell:
- Weaviate is an open source vector database.
- Weaviate allows you to store and retrieve data objects based on their semantic properties by indexing them with vectors.
- Weaviate can be used stand-alone (aka bring your vectors) or with a variety of modules that can do the vectorization for you and extend the core capabilities.
- Weaviate has a GraphQL-API to access your data easily.
- Weaviate is fast (check our open source benchmarks).
- Weaviate in detail: Weaviate is a low-latency vector database with out-of-the-box support for different media types (text, images, etc.). It offers Semantic Search, Question-Answer Extraction, Classification, Customizable Models (PyTorch/TensorFlow/Keras), etc. Built from scratch in Go, Weaviate stores both objects and vectors, allowing for combining vector search with structured filtering and the fault tolerance of a cloud-native database. It is all accessible through GraphQL, REST, and various client-side programming languages.