Comparisons // Vector Databases
Engine: StackVersus Matrix
State: Live

Qdrant vs Milvus: Vector Databases Comparison

VerdictQdrant for performance-sensitive workloads with rich payload filtering; Milvus for very large datasets that need distributed vector search.

Compare Qdrant and Milvus for vector databases: pricing, licensing, hosting, pros, cons and which one fits your team.

Built from the StackVersus tool catalog: structured pricing models, licensing, hosting and editor-curated pros and cons. Last reviewed Oct 9, 2026. Spotted something out of date? Send a correction.

Updated Oct 9, 20263 min read432 wordsIntermediatePopularity 74/100
Performance-sensitive workloads with rich payload filteringVery large datasets that need distributed vector search

Qdrant vs Milvus: Head-to-Head Comparison

Quick Verdict

Qdrant is the better pick for performance-sensitive workloads with rich payload filtering. Milvus is the better pick for very large datasets that need distributed vector search.


At a Glance

FeatureQdrantMilvus
Best ForPerformance-sensitive workloads with rich payload filteringVery large datasets that need distributed vector search
PricingFree open source; paid managed cloudFree open source; paid managed cloud
Free to StartYesYes
LicenseOpen sourceOpen source
DeploymentSelf-hosted or managed cloudSelf-hosted or managed cloud
LinkVisit QdrantVisit Milvus

Detailed Breakdown

Qdrant

High-performance vector search engine written in Rust

Pros:

  • Fast Rust core with low memory overhead
  • Powerful payload filtering
  • Quantization options to reduce memory

Cons:

  • Smaller ecosystem than older databases
  • Distributed mode requires tuning

Milvus

Cloud-native vector database built for billion-scale search

Pros:

  • Designed for billions of vectors
  • Many index types including GPU indexes
  • Managed option via Zilliz Cloud

Cons:

  • Complex distributed deployment
  • Heavier operational footprint

Key Differences

  • Positioning: Qdrant — high-performance vector search engine written in Rust. Milvus — cloud-native vector database built for billion-scale search.
  • Both share the same licensing model (open source), so the decision comes down to features and workflow fit.
  • Pricing: Qdrant — free open source; paid managed cloud. Milvus — free open source; paid managed cloud.
  • Signature strength: Qdrant — fast Rust core with low memory overhead. Milvus — designed for billions of vectors.

Frequently Asked Questions

Is Qdrant better than Milvus?

It depends on your requirements. Qdrant is a strong fit for performance-sensitive workloads with rich payload filtering, while Milvus suits very large datasets that need distributed vector search.

Is Qdrant free to use?

Yes, you can start with Qdrant for free. Pricing model: Free open source; paid managed cloud.

Is Milvus free to use?

Yes, you can start with Milvus for free. Pricing model: Free open source; paid managed cloud.

Can I self-host Qdrant or Milvus?

Qdrant can be self-hosted. Deployment options: self-hosted or managed cloud. Milvus can be self-hosted. Deployment options: self-hosted or managed cloud.

What are the main drawbacks of Qdrant and Milvus?

Qdrant: smaller ecosystem than older databases; distributed mode requires tuning. Milvus: complex distributed deployment; heavier operational footprint.

Specification Matrix

The matrix is generated from the pros/cons in the article.

Frequently Asked Questions

Is Qdrant better than Milvus?

It depends on your requirements. Qdrant is a strong fit for performance-sensitive workloads with rich payload filtering, while Milvus suits very large datasets that need distributed vector search.

Is Qdrant free to use?

Yes, you can start with Qdrant for free. Pricing model: Free open source; paid managed cloud.

Is Milvus free to use?

Yes, you can start with Milvus for free. Pricing model: Free open source; paid managed cloud.

Can I self-host Qdrant or Milvus?

Qdrant can be self-hosted. Deployment options: self-hosted or managed cloud. Milvus can be self-hosted. Deployment options: self-hosted or managed cloud.

Share & Discuss

Related in Vector Databases

Discussion

No comments yet. Start the conversation.

Disclosure: Outbound links go to official product sites. If we have an affiliate partnership, the link will be marked as such. Read the full disclosure.