vs

Milvus vs Qdrant

Milvus: Cloud-native, distributed open-source vector database built for billions of vectors. Qdrant: Rust vector search engine with rich payload filtering, quantization and a managed cloud.

key differences

  • Milvus is built for larger datasets (Multi-PB) than Qdrant (≤ 1 PB).
  • Only Milvus has change data capture, ttl / expiry, online schema changes, streaming ingest.
  • Only Qdrant has geospatial.
  • Milvus can run embedded in your application process.

choose milvus for

  • +Billion-scale semantic and image search
  • +RAG platforms serving many teams
  • +Recommendation and deduplication
  • +Multimodal retrieval over lakehouse data

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
Search Engine, Document
Document
Type
Database engine
Database engine
Status
Active
Active
Developer
LF AI & Data Foundation (developed mainly by Zilliz)
Qdrant Solutions GmbH
First release
2019
2021
Latest version
3.0.4 (Oct 26, 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
45.9
35.9
Rank
#35
#55
GitHub stars
46.5K
35.3K
Stack Overflow questions
208
60
scale & guarantees
Comfortable data size
Massive (Multi-PB)
Large (≤ 1 PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
None
None
Consistency
Tunable, Strong, Eventual
Tunable, Eventual
Schema
Strict
Schemaless
Architecture
Distributed, Shared storage, Embedded, Client server
Distributed, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
✓
✓
Serverless
—
—
Embedded
✓
—
Edge
—
—
Clouds
AWS, Google Cloud, Azure
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
Milvus API (boolean filter expressions)
Qdrant Query API (JSON filters)
Client languages
Python, Java, Go, Node.js, C#, Rust
Python, JavaScript, Rust, Go, Java, .NET
Best for
Vector search, RAG, Search
Vector search, RAG

Milvus vs Qdrant: FAQ

What is the difference between Milvus and Qdrant?

Milvus: Cloud-native, distributed open-source vector database built for billions of vectors. Qdrant: Rust vector search engine with rich payload filtering, quantization and a managed cloud. Milvus is built for larger datasets (Multi-PB) than Qdrant (≤ 1 PB). Only Milvus has change data capture, ttl / expiry, online schema changes, streaming ingest. Only Qdrant has geospatial.

When should I choose Milvus over Qdrant?

Choose Milvus for billion-scale semantic and image search; RAG platforms serving many teams; and recommendation and deduplication. Choose Qdrant for RAG retrieval with metadata filtering; recommendation and similarity search; and image and multimodal search.

Is Milvus or Qdrant more popular?

Milvus ranks #35 on the WhichDB Score (45.9/100) and Qdrant ranks #55 (35.9/100). Popularity is not fit: check the requirements that matter for your project.

Are Milvus and Qdrant open source?

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