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Tool Comparison

Chroma

Chroma

The simplest open-source vector database — get started in 3 lines of Python.

Open Source
VS
Weaviate

Weaviate

Open-source vector database with built-in embedding and hybrid search.

Open Source
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At a Glance

AttributeChromaWeaviate
License / PricingOpen SourceOpen Source
Typeaiai
GitHub Stars
Rating4.4/54.5/5
Key Features6 listed6 listed
Integrations4 listed5 listed
Categories
Vector Database
Vector Database

Key Features

Chroma

  • In-memory mode for instant prototyping
  • Persistent storage mode for production use
  • Client-server mode with REST API
  • Built-in embedding functions for OpenAI, Cohere, HuggingFace
  • Metadata filtering and full-text search
  • Simple Python and JavaScript SDKs

Weaviate

  • Built-in vectorization modules (OpenAI, Cohere, HuggingFace)
  • Hybrid search combining BM25 keyword and vector search
  • GraphQL and REST APIs
  • Multi-tenancy for SaaS applications
  • Generative search — query + LLM response in one call
  • Cloud-managed or self-hosted with Docker/Kubernetes

Real-World Use Cases

Chroma

Prototype a RAG app in minutes

pip install chromadb and create an in-memory client

Weaviate

Build generative search over your knowledge base

Start Weaviate with docker-compose (includes vectorizer module)

Integrations

Chroma

langchainllamaindexopenaihuggingface

Weaviate

langchainllamaindexopenaihuggingfacedspy

🏆 Which should you choose?

Choose Chroma if…

  • you're already in the Vector Database ecosystem and prefer Chroma's workflow
Full Chroma guide →

Choose Weaviate if…

  • you're already in the Vector Database ecosystem and prefer Weaviate's workflow
Full Weaviate guide →