vs

Chroma vs Qdrant

Chroma: Open-source retrieval database for AI apps, from embedded Python to serverless Chroma Cloud. Qdrant: Rust vector search engine with rich payload filtering, quantization and a managed cloud.

key differences

  • Qdrant is built for larger datasets (≤ 1 PB) than Chroma (≤ 10 TB).
  • Transactions: Chroma offers limited ACID; Qdrant offers none.
  • Only Chroma has branching.
  • Only Qdrant has geospatial, compression, role-based access.
  • Chroma has a serverless option; Qdrant does not.
  • Chroma can run embedded in your application process.

choose chroma for

  • +Prototyping RAG in notebooks
  • +Embedded retrieval in Python apps
  • +Agent memory
  • +Serverless RAG backends

best at · Vector search, RAG, Search

choose qdrant for

  • +RAG retrieval with metadata filtering
  • +Recommendation and similarity search
  • +Image and multimodal search
  • +Multi-tenant semantic search

best at · Vector search, RAG

overview
Primary model
Vector
Vector
Also supports
Document, Search Engine
Document
Type
Database engine
Database engine
Status
Active
Active
Developer
Chroma
Qdrant Solutions GmbH
First release
2023
2021
Latest version
1.5.9 (May 5, 2026)
1.20.0 (Oct 22, 2026)
License
Open source (permissive)Apache License 2.0
Open source (permissive)Apache License 2.0
Free tier
✓
✓
popularity
WhichDB Score
49.0
35.9
Rank
#29
#55
GitHub stars
29.6K
35.3K
Stack Overflow questions
266
60
scale & guarantees
Comfortable data size
Medium (≤ 10 TB)
Large (≤ 1 PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
Limited
None
Consistency
Eventual
Tunable, Eventual
Schema
Schemaless
Schemaless
Architecture
Embedded, Single node, Serverless, Client server
Distributed, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
✓
✓
Serverless
✓
—
Embedded
✓
—
Edge
—
—
Clouds
AWS
AWS, Google Cloud, Azure
capabilities
Transactions
—
—
Joins
—
—
Secondary indexes
✓
✓
Full-text search
✓
✓
Vector search
✓
✓
Geospatial
—
✓
JSON
✓
✓
Change data capture
—
—
Triggers
—
—
Stored procedures
—
—
Materialized views
—
—
TTL / expiry
—
—
Pub/Sub
—
—
Columnar storage
—
—
In-memory
—
—
Durable persistence
✓
✓
Compression
—
✓
Encryption at rest
—
—
Role-based access
—
✓
Time travel
—
—
Branching
✓
—
Online schema changes
—
—
Streaming ingest
—
—
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
Chroma API (where filters)
Qdrant Query API (JSON filters)
Client languages
Python, JavaScript, Rust
Python, JavaScript, Rust, Go, Java, .NET
Best for
Vector search, RAG, Search, Embedded
Vector search, RAG

Chroma vs Qdrant: FAQ

What is the difference between Chroma and Qdrant?

Chroma: Open-source retrieval database for AI apps, from embedded Python to serverless Chroma Cloud. Qdrant: Rust vector search engine with rich payload filtering, quantization and a managed cloud. Qdrant is built for larger datasets (≤ 1 PB) than Chroma (≤ 10 TB). Transactions: Chroma offers limited ACID; Qdrant offers none. Only Chroma has branching.

When should I choose Chroma over Qdrant?

Choose Chroma for prototyping RAG in notebooks, embedded retrieval in Python apps and agent memory. Choose Qdrant for RAG retrieval with metadata filtering; recommendation and similarity search; and image and multimodal search.

Is Chroma or Qdrant more popular?

Chroma ranks #29 on the WhichDB Score (49.0/100) and Qdrant ranks #55 (35.9/100). Popularity is not fit: check the requirements that matter for your project.

Are Chroma and Qdrant open source?

Yes. Chroma is open source. License: Apache License 2.0. Yes. Qdrant is open source. License: Apache License 2.0.