Weaviate is an open-source, cloud-native vector database that stores both objects and vectors and enables semantic search at scale. It converts text, images and other data into embeddings, then provides fast nearest-neighbor vector search combined with keyword/structured filtering, retrieval-augmented generation (RAG) and reranking within a single query interface. Weaviate exposes GraphQL and REST APIs (and gRPC in newer versions) and offers official client libraries so applications can integrate semantic search, recommender systems, chatbots and other retrieval-driven workflows. Its design emphasizes low-latency nearest-neighbor queries, extensibility via modular vectorizers and rerankers, and deployment flexibility (self-hosted, Docker, embedded or cloud deployments).