Weaviate

Weaviate is an open-source vector database designed for AI applications, providing scalable storage and retrieval of vector embeddings alongside traditional data. Weaviate supports hybrid search (combining vector similarity with keyword filtering), multi-modal data, and built-in vectorization modules that can automatically generate embeddings from text, images, and other data types.

Weaviate's architecture is designed for production AI workloads: it supports horizontal scaling, multi-tenancy, real-time data ingestion, and ACID-compliant transactions. The platform integrates with all major AI frameworks and can be deployed as a managed cloud service or self-hosted.

In the database and vector store layer, Weaviate provides the persistent memory infrastructure that AI agents need to store and retrieve knowledge, maintaining the context and recall capabilities that make agents useful in real-world applications.