Weaviate

Weaviate is an open-source vector database that stores data objects and vector embeddings, enabling AI-native applications with semantic search, recommendation, and classification capabilities. It combines vector search with structured filtering and can be deployed anywhere. Key features include hybrid search combining vector and keyword search, multi-modal search across text, images, and other data types, GraphQL and REST APIs for easy integration, modular architecture with pluggable ML models, support for various embedding models (OpenAI, Cohere, Hugging Face), built-in vectorization modules, horizontal scaling capabilities, CRUD operations on objects and vectors, and both cloud-hosted and self-hosted options. Weaviate is used for building RAG applications, semantic search engines, recommendation systems, and intelligent data platforms.