Chroma vs Qdrant
A neutral, data-driven comparison — live metrics, use-case guidance and FAQ to help you pick.
At a glance
| Chroma | Qdrant | |
|---|---|---|
| GitHub stars | 28,456 | 32,389 |
| PyPI downloads / mo | 13,590,061 | 23,963,183 |
| License | Apache-2.0 | Apache-2.0 |
| Type | database | database |
| Self-hostable | Yes | Yes |
| Managed option | Chroma Cloud | Qdrant Cloud |
| Latest release | 1.5.9 | v1.18.2 |
Which should you choose?
Choose Chroma if…
- You're building a local prototype or small RAG app and want the simplest start
- You want an embedded, Python-first experience
- Ease of use matters more than large-scale production features
Choose Qdrant if…
- You're deploying to production and need scale, performance and strong filtering
- You want a standalone server (Rust) with a managed cloud option
- You expect to grow beyond a single-machine prototype
Chroma is the easiest way to start — great for local prototypes and small RAG apps; Qdrant is built for production scale and filtered search. Many teams prototype on Chroma and move to Qdrant (or another production DB) as they grow.
What they are
Chroma: Search infrastructure for AI
Qdrant: Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
FAQ
Is Chroma production-ready?
Chroma is excellent for prototyping and smaller apps; for large-scale production with high concurrency, a server-based engine like Qdrant is often a better fit.
Which is easier to start with?
Chroma — it's embedded and Python-first, ideal for quick local experiments.
Can both do metadata filtering?
Yes, both support filtered vector search; Qdrant is known for advanced payload filtering at scale.
Are both open-source?
Yes — Chroma (Apache-2.0) and Qdrant (Apache-2.0), each with a managed cloud option.