vs

Marqo vs Qdrant

Marqo: End-to-end tensor search engine that embeds text and images for you, built on Vespa. 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 Marqo (≤ 10 TB).
  • Horizontal scaling is addon in Marqo and native in Qdrant.
  • Only Qdrant has geospatial, compression, role-based access.

choose marqo for

  • +Multimodal product and image search
  • +Prototyping semantic search without an embedding pipeline
  • +E-commerce discovery

best at · Vector search, Search, RAG

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
Marqo
Qdrant Solutions GmbH
First release
2022
2021
Latest version
2.26.0 (Apr 7, 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
14.5
35.9
Rank
#229
#55
GitHub stars
5K
35.3K
Stack Overflow questions
–
60
scale & guarantees
Comfortable data size
Medium (≤ 10 TB)
Large (≤ 1 PB)
Horizontal scaling
Addon
Native
Multi-region
None
None
ACID
None
None
Consistency
Eventual
Tunable, Eventual
Schema
Flexible
Schemaless
Architecture
Single node, Client server
Distributed, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
✓
✓
Serverless
—
—
Embedded
—
—
Edge
—
—
Clouds
–
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
Marqo search API (JSON)
Qdrant Query API (JSON filters)
Client languages
Python, JavaScript
Python, JavaScript, Rust, Go, Java, .NET
Best for
Vector search, Search, RAG
Vector search, RAG

Marqo vs Qdrant: FAQ

What is the difference between Marqo and Qdrant?

Marqo: End-to-end tensor search engine that embeds text and images for you, built on Vespa. Qdrant: Rust vector search engine with rich payload filtering, quantization and a managed cloud. Qdrant is built for larger datasets (≤ 1 PB) than Marqo (≤ 10 TB). Horizontal scaling is addon in Marqo and native in Qdrant. Only Qdrant has geospatial, compression, role-based access.

When should I choose Marqo over Qdrant?

Choose Marqo for multimodal product and image search; prototyping semantic search without an embedding pipeline; and E-commerce discovery. Choose Qdrant for RAG retrieval with metadata filtering; recommendation and similarity search; and image and multimodal search.

Is Marqo or Qdrant more popular?

Qdrant ranks #55 on the WhichDB Score (35.9/100) and Marqo ranks #229 (14.5/100). Popularity is not fit: check the requirements that matter for your project.

Are Marqo and Qdrant open source?

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