weaviate and weaviate-io
The main repository contains the vector database implementation itself, while the secondary repository hosts the documentation and marketing website for that same database product, making them ecosystem siblings where one is the core software and the other is its web presence.
About weaviate
weaviate/weaviate
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Built in Go for millisecond-scale performance on billions of vectors, Weaviate integrates vectorization from major providers (OpenAI, Cohere, HuggingFace) at import time or accepts pre-computed embeddings. It unifies semantic search, BM25 keyword filtering, image search, and generative RAG/reranking in a single query interface, with production features including horizontal scaling, multi-tenancy, replication, and RBAC for enterprise deployments.
About weaviate-io
weaviate/weaviate-io
Website for the Weaviate vector database
Built with Docusaurus 2, this static site generator uses Node.js and yarn for dependency management, with automated link checking during builds. Code examples are dynamically extracted from tested scripts using custom JSX components, ensuring accuracy across Python, TypeScript, and other language tabs. The site deploys via GitHub Pages and integrates with the separate docs repository for centralized documentation maintenance.
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