vs

Marqo vs Weaviate

Marqo: End-to-end tensor search engine that embeds text and images for you, built on Vespa. Weaviate: Open-source AI-native vector database with hybrid search, modules for embeddings and multi-tenancy.

key differences

  • Weaviate is built for larger datasets (≤ 1 PB) than Marqo (≤ 10 TB).
  • Horizontal scaling is addon in Marqo and native in Weaviate.
  • Only Weaviate 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 weaviate for

  • +RAG over documents with hybrid retrieval
  • +Multi-tenant SaaS semantic search
  • +Product and content recommendation
  • +Agent memory stores

best at · Vector search, RAG, Search

overview
Primary model
Vector
Vector
Also supports
Search Engine, Document
Document, Search Engine
Type
Database engine
Database engine
Status
Active
Active
Developer
Marqo
Weaviate B.V.
First release
2022
2019
Latest version
2.26.0 (Apr 7, 2026)
1.40.2 (Oct 22, 2026)
License
Open source (permissive)Apache License 2.0
Open source (permissive)BSD-3-Clause (core); enterprise features under the Weaviate License
Free tier
✓
✓
popularity
WhichDB Score
14.5
33.4
Rank
#229
#65
GitHub stars
5K
16.9K
Stack Overflow questions
–
160
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
Flexible
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)
GraphQL, Weaviate query API
Client languages
Python, JavaScript
Python, TypeScript, Go, Java, C#
Best for
Vector search, Search, RAG
Vector search, RAG, Search

Marqo vs Weaviate: FAQ

What is the difference between Marqo and Weaviate?

Marqo: End-to-end tensor search engine that embeds text and images for you, built on Vespa. Weaviate: Open-source AI-native vector database with hybrid search, modules for embeddings and multi-tenancy. Weaviate is built for larger datasets (≤ 1 PB) than Marqo (≤ 10 TB). Horizontal scaling is addon in Marqo and native in Weaviate. Only Weaviate has geospatial, compression, role-based access.

When should I choose Marqo over Weaviate?

Choose Marqo for multimodal product and image search; prototyping semantic search without an embedding pipeline; and E-commerce discovery. Choose Weaviate for RAG over documents with hybrid retrieval; multi-tenant SaaS semantic search; and product and content recommendation.

Is Marqo or Weaviate more popular?

Weaviate ranks #65 on the WhichDB Score (33.4/100) and Marqo ranks #229 (14.5/100). Popularity is not fit: check the requirements that matter for your project.

Are Marqo and Weaviate open source?

Yes. Marqo is open source. License: Apache License 2.0. Yes. Weaviate is open source. License: BSD-3-Clause (core); enterprise features under the Weaviate License.