Vector Database
16.1k 2026-04-26
weaviate/weaviate
An open-source, cloud-native vector database enabling semantic search at scale by combining vector similarity with structured filtering and AI capabilities.
Core Features
Stores both objects and vectors for hybrid search.
Supports Retrieval-Augmented Generation (RAG) and reranking.
Automatic vectorization with integrated models (OpenAI, HuggingFace).
Cloud-native architecture with multi-tenancy, replication, and RBAC.
Scalable and fault-tolerant for production deployments.
Quick Start
docker compose up -dDetailed Introduction
Weaviate is a powerful open-source, cloud-native vector database designed for building intelligent applications that require semantic understanding. It uniquely stores both objects and their corresponding vector embeddings, allowing for sophisticated queries that combine vector similarity search with traditional structured filtering. This capability is crucial for modern AI applications like RAG systems, semantic search, recommendation engines, and chatbots, providing a scalable, fault-tolerant, and efficient solution for managing and querying high-dimensional data.