# Weaviate

> Weaviate is an open-source, cloud-native vector database with GraphQL API, supporting hybrid search (vector+keyword), modules for ML integrations. It features HNSW indexing and auto-vectorization. Excels in knowledge graphs and multimodal RAG; vs Qdrant more schema-aware and modular.

- **URL:** https://weaviate.io/
- **Category:** Core Vector Databases
- **Tags:** Graphql, Modular Ml
- **Updated:** 2026-04-30 11:38
- **Canonical page:** https://vectordb.ever.works/items/weaviate

## Details

## Overview

Open-source AI-native vector database designed for scalable semantic search and knowledge graphs, with GraphQL API and modular extensions.

## Features

- GraphQL API for querying
- Hybrid search: vector similarity + keyword (BM25)
- Modules ecosystem for ML integrations (e.g., text2vec, auto-classification)
- Multi-tenancy support
- Deployment flexibility: self-hosted, cloud (Weaviate Cloud), embedded/serverless
- HNSW indexing, structured filtering

## Use Cases

- Semantic search applications
- Knowledge graphs and RAG pipelines
- Multimodal data retrieval

## Pricing

Free and open-source (BSD-3-Clause license). Enterprise support via Weaviate Cloud.

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