Weaviate is an open-source vector database that allows users to store data objects and vector embeddings from ML-models and scale to billions of data objects seamlessly. The tool provides lightning-fast pure vector similarity search over data objects or raw vectors and supports a combination of keyword-based search and vector search techniques for state-of-the-art search results. Weaviate also enables users to use any generative model in combination with your data to create next-gen search experiences. The tool has integrations with a wide variety of well-known neural search frameworks and provides out-of-the-box support for vectorization. Users can also choose from Weaviate’s modules, which have extensive support for vectorization. Weaviate is designed to give developers an excellent experience and enable them to go from zero to production seamlessly. The tool is designed with community and open-source principles in mind, and users can join the Weaviate community on Slack. The tool currently has backup and restore capabilities, making it a robust solution for data-intensive applications. Weaviate has a vast library of resources that help users learn how to use the tool and get inspiration from other users’ innovative apps. Finally, Weaviate is available for use anywhere as an open-source tool.