vioscaleAI
Comparison

Ray vs ZenML

On the evidence we track, Ray leads this comparison with a composite score of 71/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.

Ray full profile →ZenML full profile →
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★Ray71
ZenML61
Score
vioscaleAI score
Ray71 / 100medium · 65%
ZenML61 / 100medium · 52%
Pricing
Free tier
Ray✓
ZenML✓
Model
Price level
Rayfree
ZenMLlow
Transparent
Ray–
ZenML✗
Integrations
Count
Ray17
ZenML60
Security
Certifications
Iso27001
Ray–
ZenML✓
Scorecard
Ray5.7
ZenML6.8
Soc2
Ray–
ZenML✓
Trust center
Vulnerabilities
Reliability
Status page
Ray✓
ZenML✓
Adoption
Dependent repos
Ray3,641
ZenML44
Github stars
Ray44,036
ZenML5,615
Package downloads weekly
Ray11,291,327
ZenML–
Activity
Commits last 30d
Ray100
ZenML41
Release
Cadence days
Ray18
ZenML15
History
License
Spdx
Language
Primary
RayPython
ZenMLPython
Market
Availability
Content
Faq

Capabilities

Feature-by-feature on the axes that matter for mlops & llmops tools. “-” means undocumented, not absent.

Core
Tool role
RayAgent / RAG framework
ZenMLEnd-to-end ML platform
Deployment
Self-hostable / OSS core
Ray✓
ZenML✓
Managed cloud available
Ray✓
ZenML✓
On-prem / VPC deployment
Ray✓
ZenML✓
Observability
LLM tracing / observability
Ray✓
ZenML✓
Evaluation (offline / LLM-judge / human)
Ray-
ZenML✓
Dev
Prompt management + versioning
Ray-
ZenML✓
Tracking
Experiment tracking / model registry
Ray✓
ZenML✓
Serving
Model serving / inference endpoint
Ray✓
ZenML✓
Interop
OpenTelemetry / OpenLLMetry compatible
Ray✓
ZenML✓
Framework-agnostic
Ray✓
ZenML✓
Gateway
Multi-provider model support
Ray✓
ZenML✓
Data
No-train-on-customer-data guarantee
Ray-
ZenML-

What each one is

The product in its own terms, so the numbers below have context.

Ray

Leader

Open-source framework for building and scaling distributed ML and Python applications, supporting the full pipeline from data processing and model training to inference and serving with simple APIs.

Independently observed

ZenML

ZenML is a Python-based orchestration framework that manages machine learning pipelines and agents across any infrastructure, from local development to production Kubernetes clusters. It provides centralized artifact management, automated tracking and versioning, and enterprise-grade security compliance for reproducible AI systems.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

Ray

Leader
Open source
as of verify ↗

ZenML

HybridFree tier

Free open-source version; managed Pro service available

  • CommunityFree
    • experiment tracking
    • pipeline orchestration
    • artifact storage
    • model versioning
  • ProManaged service pricing not specified
    • managed control plane
    • governance
    • SSO
    • SLA support
    • audit trails
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
macOS
Ray✗
ZenML✓
Windows
Ray✗
ZenML✓
Linux
Ray✗
ZenML✓
CLI
Ray✓
ZenML✓
Deployment
Cloud / SaaS
Ray✓
ZenML✓
Self-hosted
Ray✓
ZenML✓
Hybrid
Ray✗
ZenML✓

Integrations

What each product connects to. Counts come from the vendor's own integration directory where one exists.

In common (5)
  • PyTorch
  • Kubernetes
  • AWS
  • Azure
  • Databricks

Ray

Leader
27 total - 22 not shared
  • TensorFlow
  • AIBrix
  • AReaL
  • Cosmos Curate
  • Daft
  • Data-Juicer
  • DeltaCAT
  • Modin
  • NeMo Curator
  • NeMo-RL
  • OpenRLHF
  • RayDP
  • ROLL
  • SkyRL
  • SLIME
  • Syftr
  • verl
  • vLLM
  • GCP
  • DeltaLake
  • Spark
  • Pandas
Independently observed

ZenML

26 total - 21 not shared
  • Git
  • GitHub
  • GitLab
  • Docker
  • Poetry
  • Slack
  • ClickUp
  • MLflow
  • Trackio
  • OpenAI
  • LangGraph
  • scikit-learn
  • Hugging Face
  • LlamaIndex
  • PyTorch Lightning
  • Axolotl
  • AzureML
  • Google Cloud
  • DigitalOcean
  • Kubeflow
  • MySQL
Independently observed
Still deciding?

Ray or ZenML: which one depends on you

A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.

Free to run, no account needed to start. How the evaluation works

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.