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Weaviate is an open-source, cloud-native vector database that goes beyond traditional vector storage by combining vector search with structured database capabilities. It allows developers to store both data objects and their corresponding vector embeddings in a single place, enabling hybrid search that merges keyword-based BM25 search with semantic vector search for highly accurate results.

With built-in modules for popular AI models, Weaviate can automatically vectorize data upon ingestion, simplifying development workflows. It is highly optimized for Retrieval-Augmented Generation (RAG), question-answering systems, and classification tasks. The platform offers flexible deployment options, including self-hosted open-source setups, managed cloud services, and hybrid deployments to accommodate various enterprise security requirements.