Cloudera AI Registry vs JFrog ML

Cloudera AI Registry9.2Visit JFrog ML8.6Visit

Higher score Cloudera AI Registry #2 in Model Registry Software 9.2/10 Pricing on request ✓ 4 of 6 features Visit Cloudera

vs

JFrog ML #6 in Model Registry Software 8.6/10 Pricing on request ✓ 4 of 6 features Visit JFrog ML

• Cloudera AI Registry fits best

  Cloudera platform users

• JFrog ML fits best

  Teams prioritizing secure model supply chains

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Side by side

Feature	Cloudera AI Registry 9.2/10 Visit ↗	JFrog ML 8.6/10 Visit ↗
At a glance
Editor score	9.2	8.6
Ranking	#2 in Model Registry Software	#6 in Model Registry Software
Best for	Cloudera platform users	Teams prioritizing secure model supply chains
Pricing model	Paid	Paid
Starting price	Pricing on request	—
Free plan	Not checked yet	—
Free trial	—	—
Deployment	Cloud	Cloud, Self-hosted
Platforms	Web	Web
Support	Phone, Community, Docs	Docs
Integrations	4 integrations	4 integrations
Built for	Enterprise, Mid-market	Mid-market, Enterprise
Features Cloudera AI Registry 4/6 · JFrog ML 4/6
Model versioning	✓	✓
Approval workflows	Not checked yet	Not checked yet
Model lineage	✓	✓
Deployment tracking	✓	✓
Model aliases	Not checked yet	Not checked yet
Artifact storage	✓	✓
Our review
Pros	Tracks model versions, metadata, lineage, archives, and deployment details Provides REST and CLI APIs for model operations and registry queries Connects with MLflow, CI/CD pipelines, NVIDIA NGC, and Hugging Face	Immutable model and artifact versioning through JFrog Artifactory Canary, A/B, and shadow deployment strategies Security scanning with JFrog Xray and approval governance
Cons	Best suited to organizations already using Cloudera AI environments Cloud delivery runs within Cloudera environments on AWS or Azure Pricing is handled through contact sales rather than a published registry rate	No free plan Pricing requires contact with sales Broader MLOps scope may exceed registry-only needs
Our verdict	Cloudera AI Registry gives organizations using Cloudera AI a central place to store and organize machine learning models, model archives, versions, metadata, dependencies, and performance information. It is aimed at enterprise MLOps… Read the review →	JFrog ML is an MLOps platform for data scientists, ML engineers, AI developers, and DevOps teams. Its centralized model registry supports the path from research to production, with model building, training, testing, packaging, deployment,… Read the review →

Strengths and trade-offs

• Cloudera AI Registry — where it wins

  • Tracks model versions, metadata, lineage, archives, and deployment details
  • Provides REST and CLI APIs for model operations and registry queries
  • Connects with MLflow, CI/CD pipelines, NVIDIA NGC, and Hugging Face

  Where it doesn't

  • Best suited to organizations already using Cloudera AI environments
  • Cloud delivery runs within Cloudera environments on AWS or Azure
  • Pricing is handled through contact sales rather than a published registry rate

• JFrog ML — where it wins

  • Immutable model and artifact versioning through JFrog Artifactory
  • Canary, A/B, and shadow deployment strategies
  • Security scanning with JFrog Xray and approval governance

  Where it doesn't

  • No free plan
  • Pricing requires contact with sales
  • Broader MLOps scope may exceed registry-only needs

• Cloudera AI Registry9.2/10 · Pricing on request

  A focused model registry for teams operating machine learning workflows in Cloudera AI.

  Visit ClouderaFull verdict →
• JFrog ML8.6/10 · Pricing on request

  A centralized registry for teams that need governed, versioned model delivery.

  Visit JFrog MLFull verdict →