Comparison

Qdrant vs Weaviate

Overview

High-performance vector database for the next generation of AI apps.

Qdrant is an open-source vector database and similarity-search engine written in Rust. It stores embeddings with rich payload filtering and is used for retrieval-augmented generation (RAG), semantic search and recommendation systems, with a managed cloud option.

Weaviate

Open-source AI-native vector database.

weaviate.io →

Weaviate is an open-source, AI-native vector database with built-in vectorization modules and hybrid search. It combines vector and keyword search, integrates with popular embedding and generative models, and offers a managed cloud service.

Which should you choose?

Both are open-source with a free tier and managed cloud options. Qdrant emphasizes raw ANN search performance and payload filtering; Weaviate emphasizes built-in vectorizer modules and hybrid vector+keyword search with a GraphQL API. Choose Qdrant for maximum search performance and filtering control; choose Weaviate if built-in vectorization and hybrid search out of the box matter more.

TLDR

—If maximum search performance and filtering control matter most, choose Qdrant.
—If you want built-in vectorization and hybrid search out of the box, choose Weaviate.