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Marqo vs Milvus

A side-by-side comparison of Marqo and Milvus, two Vector DB tools, drawn from Ignaite's continuously-verified listings.

Compared from listings verified as of

Marqo

Vector DB

AI-native vector search for multimodal product discovery.

View Marqo

Milvus

Vector DB

Distributed vector database built for billion-scale search.

View Milvus

At a glance

Feature comparison of Marqo and Milvus
AttributeMarqoMilvus
CategoryVector DBVector DB
Pricing (differs)PAIDFREEMIUM
License (differs)ProprietaryOpen core
Deployment (differs)CloudHybrid
Platforms (differs)API, WebAPI
Model supportModel-agnosticModel-agnostic
Vendor (differs)MarqoZilliz

The honest brief

Marqo

Bundles embedding generation, storage, and retrieval behind one API and can train a model on your own catalog — no separate embedding pipeline to wire up.

  • Generates and stores embeddings in-engine
  • Native multimodal (text + image) search
  • Turnkey ecommerce platform integrations
  • Backed by Lightspeed and Blackbird
  • Open-source engine is deprecated, no longer updated
  • No public pricing; commercial product is sales-led
  • Scope narrowed toward ecommerce search

Milvus

Storage/compute split plus DiskANN make it the most robust open-source choice at billion-vector scale.

  • Scales to billion-vector deployments
  • Storage/compute separation
  • Many index types (HNSW, IVF, DiskANN) + GPU
  • Mature project with a large community
  • Operationally heavy to self-host
  • Overkill for small workloads
  • Performance hinges on data quality
  • Higher latency than Qdrant at p50