Comparison

MLflow vs Ray

No clear leader: Ray (70.8) and MLflow (70.4) are within the 5-point margin; treat as a tie. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.

MLflow full profile →Ray full profile →

Machine formatsMarkdownJSONGraphQLMarkdown is open. JSON and GraphQL need a free key.

MLflow70

Ray71

Attribute comparison across 2 tools
Attribute	MLflow	Ray
vioscaleAI score	70 / 100medium · 67%	71 / 100medium · 65%
Pricing
Free tierpricing.free_tier	✓	✓
Modelpricing.model	open_source	commercial
Price levelpricing.price_level	free	free
Transparentpricing.transparent	✓	-
Integrations
Countintegrations.count	9	17
Security
Scorecardsecurity.scorecard	5.4	5.7
Trust centersecurity.trust_center	https://mlflow.org/articles/tags/ai-compliance-policies/	-
Vulnerabilitiessecurity.vulnerabilities	Count: 82 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=mlflow&per_page=100 · Last 12m: 29 · Max severity: CRITICAL	Count: 12 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=ray&per_page=100 · Last 12m: 6 · Max severity: CRITICAL
Reliability
Status pagereliability.status_page	-	✓
Adoption
Dependent reposadoption.dependent_repos	5,089	3,641
Github starsadoption.github_stars	28,260	44,036
Package downloads weeklyadoption.package_downloads_weekly	9,993,245	11,291,327
Activity
Commits last 30dactivity.commits_last_30d	100	100
Release
Cadence daysrelease.cadence_days	9	18
Historyrelease.history	20 items	20 items
License
Spdxlicense.spdx	Apache-2.0	Apache-2.0
Language
Primarylanguage.primary	Python	Python
Content
Faqcontent.faq	6 items	6 items

Score

vioscaleAI score

MLflow70 / 100medium · 67%

Ray71 / 100medium · 65%

Pricing

Free tier

MLflow✓

Ray✓

Model

MLflowopen_source

Raycommercial

Price level

MLflowfree

Rayfree

Transparent

MLflow✓

Ray–

Integrations

Count

MLflow9

Ray17

Security

Scorecard

MLflow5.4

Ray5.7

Trust center

MLflowhttps://mlflow.org/articles/tags/ai-compliance-policies/

Ray–

Vulnerabilities

MLflowCount: 82 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=mlflow&per_page=100 · Last 12m: 29 · Max severity: CRITICAL

RayCount: 12 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=ray&per_page=100 · Last 12m: 6 · Max severity: CRITICAL

Reliability

Status page

MLflow–

Ray✓

Adoption

Dependent repos

MLflow5,089

Ray3,641

Github stars

MLflow28,260

Ray44,036

Package downloads weekly

MLflow9,993,245

Ray11,291,327

Activity

Commits last 30d

MLflow100

Ray100

Release

Cadence days

MLflow9

Ray18

History

MLflow20 items

Ray20 items

License

Spdx

MLflowApache-2.0

RayApache-2.0

Language

Primary

MLflowPython

RayPython

Content

Faq

MLflow6 items

Ray6 items

Capabilities

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

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

Core

Tool role

MLflowEnd-to-end ML platform

RayAgent / RAG framework

Deployment

Self-hostable / OSS core

MLflow✓

Ray✓

Managed cloud available

MLflow✓

Ray✓

On-prem / VPC deployment

MLflow✓

Ray✓

Observability

LLM tracing / observability

MLflow✓

Ray✓

Evaluation (offline / LLM-judge / human)

MLflow✓

Ray-

Dev

Prompt management + versioning

MLflow✓

Ray-

Tracking

Experiment tracking / model registry

MLflow✓

Ray✓

Serving

Model serving / inference endpoint

MLflow✓

Ray✓

Interop

OpenTelemetry / OpenLLMetry compatible

MLflow✓

Ray✓

Framework-agnostic

MLflow✓

Ray✓

Gateway

Multi-provider model support

MLflow✓

Ray✓

Data

No-train-on-customer-data guarantee

MLflow-

Ray-

What each one is

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

MLflow

A comprehensive platform that helps teams debug, evaluate, monitor, and optimize production AI applications. Provides experiment tracking, prompt management, model deployment, systematic evaluation tools, and a unified API gateway for managing access to multiple LLM providers with cost controls.

Independently observed

Ray

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

Pricing

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

MLflow

Open source

as of 2026-10-05verify ↗

Ray

Open source

as of 2026-09-14verify ↗

Platform & deployment

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

Platform and deployment support comparison
Supports	MLflow	Ray
WebPlatforms	✓	✗
CLIPlatforms	✓	✓
Cloud / SaaSDeployment	✓	✓
Self-hostedDeployment	✓	✓
On-premiseDeployment	✓	✗

Platforms

Web

MLflow✓

Ray✗

CLI

MLflow✓

Ray✓

Deployment

Cloud / SaaS

MLflow✓

Ray✓

Self-hosted

MLflow✓

Ray✓

On-premise

MLflow✓

Ray✗

Integrations

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

In common (2)

Databricks
Kubernetes

MLflow

32 total - 30 not shared

AWS S3
Google Cloud Storage
Azure Storage
AzureML
LangChain
Pydantic AI
Anthropic Claude
OpenAI
Google Gemini
SAP AI Core
JFrog
Aliyun
PostgreSQL
MySQL
MSSQL
Claude Code
OpenAI Codex
Gemini
Anthropic
Ollama
OpenClaw
Qwen Code
LiteLLM
Amazon S3
+6 more

Independently observed

Ray

27 total - 25 not shared

PyTorch
TensorFlow
AIBrix
AReaL
Cosmos Curate
Daft
Data-Juicer
DeltaCAT
Modin
NeMo Curator
NeMo-RL
OpenRLHF
RayDP
ROLL
SkyRL
SLIME
Syftr
verl
vLLM
AWS
GCP
Azure
DeltaLake
Spark
+1 more

Independently observed

Still deciding?

MLflow or Ray: 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.