# MLflow vs Ray

| Attribute | MLflow | Ray |
|---|---|---|
| **vioscaleAI score** | 70.4 (67% (medium)) | 70.8 (65% (medium)) |
| activity.commits_last_30d | 100 | 100 |
| adoption.dependent_repos | 5,089 | 3,641 |
| adoption.github_stars | 28,260 | 44,036 |
| adoption.package_downloads_weekly | 9,993,245 | 11,291,327 |
| content.faq | `[{"answer":"A comprehensive, open-source platform that provides experiment tracking, model registry, LLM tracing, prompt management, and deployment capabilities across the complete machine learning and AI lifecycle It is indexed under MLOps & LLMOps Tools.","source":"https://mlflow.org","question":"What is MLflow?","confidence":0.6},{"answer":"MLflow is open source, so it can be self-hosted and used at no licence cost. It is released under the Apache-2.0 licence. Pricing changes often, so verify at source before relying on it.","source":"https://mlflow.org","question":"Is MLflow free to use?","confidence":0.6},{"answer":"MLflow supports the web and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://mlflow.org","question":"What platforms does MLflow support?","confidence":0.6},{"answer":"Yes. MLflow can be deployed cloud / SaaS and self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://mlflow.org","question":"Can MLflow be self-hosted?","confidence":0.6},{"answer":"We have confirmed 24 integrations for MLflow, including Databricks, AWS S3, Google Cloud Storage, Azure Storage, AzureML, Kubernetes, LangChain and Pydantic AI, plus 16 more. This is what we could verify from public sources, so the vendor may support others we have not indexed.","source":"https://mlflow.org","question":"What does MLflow integrate with?","confidence":0.6},{"answer":"Yes. MLflow is published under the Apache-2.0 licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.","source":"https://github.com/mlflow/mlflow","question":"Is MLflow open source?","confidence":0.95}]` | `[{"answer":"Ray is an open-source unified framework for scaling Python and machine learning applications across any infrastructure. It provides distributed compute primitives, specialized AI libraries for data processing, model training, tuning, and serving, with seamless scaling from development environments to large clusters. It is indexed under MLOps & LLMOps Tools.","source":"https://www.ray.io","question":"What is Ray?","confidence":0.6},{"answer":"Ray offers a free tier, so you can start without paying. Pricing changes often, so verify at source before relying on it.","source":"https://www.ray.io","question":"Is Ray free?","confidence":0.6},{"answer":"Ray supports a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://www.ray.io","question":"What platforms does Ray support?","confidence":0.6},{"answer":"Yes. Ray can be deployed cloud / SaaS, hybrid, on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://www.ray.io","question":"Can Ray be self-hosted?","confidence":0.6},{"answer":"We have confirmed 19 integrations for Ray, including PyTorch, TensorFlow, AIBrix, AReaL, Cosmos Curate, Daft, Data-Juicer and DeltaCAT, plus 11 more. This is what we could verify from public sources, so the vendor may support others we have not indexed.","source":"https://www.ray.io","question":"What does Ray integrate with?","confidence":0.6},{"answer":"Yes. Ray is published under the Apache-2.0 licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.","source":"https://github.com/ray-project/ray","question":"Is Ray open source?","confidence":0.67}]` |
| deployment.options | `{"cloud":true,"on_prem":true,"self_hosted":true}` | `{"cloud":true,"self_hosted":true}` |
| description.long | 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. | 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. |
| features.capabilities | `{"role":"platform","evaluation":true,"open_source":true,"managed_cloud":true,"model_serving":true,"pricing_model":"free_open_source","rate_limiting":true,"self_hostable":true,"multi_provider":true,"vpc_deployment":true,"otel_compatible":true,"deployment_model":"self-hosted","llm_observability":true,"prompt_management":true,"streaming_support":true,"architecture_model":"open_source_proxy","framework_agnostic":true,"experiment_tracking":true,"budget_spend_controls":true,"guardrails_moderation":"built-in","openai_compatible_api":true,"request_cost_observability":true,"mit_or_apache_permissive_oss_license":true,"auto_fallback_routing_on_rate_limit_or_downtime":true,"organization_wide_cost_tracking_and_chargebacks":true}` | `{"role":"framework","managed_cloud":true,"model_serving":true,"self_hostable":true,"multi_provider":true,"vpc_deployment":true,"otel_compatible":true,"llm_observability":true,"framework_agnostic":true,"experiment_tracking":true}` |
| integrations.count | 9 | 17 |
| integrations.list | `[{"name":"Databricks"},{"name":"AWS S3"},{"name":"Google Cloud Storage"},{"name":"Azure Storage"},{"name":"AzureML"},{"name":"Kubernetes"},{"name":"LangChain"},{"name":"Pydantic AI"},{"name":"Anthropic Claude"},{"name":"OpenAI"},{"name":"Google Gemini"},{"name":"SAP AI Core"},{"name":"JFrog"},{"name":"Aliyun"},{"name":"PostgreSQL"},{"name":"MySQL"},{"name":"MSSQL"},{"name":"Claude Code"},{"name":"OpenAI Codex"},{"name":"Gemini"},{"name":"Anthropic"},{"name":"Ollama"},{"name":"OpenClaw"},{"name":"Qwen Code"},{"name":"LiteLLM"},{"name":"Amazon S3"},{"name":"OpenTelemetry/OTLP"},{"name":"OpenAI-compatible endpoints"},{"name":"OpenTelemetry","native":true,"category":"observability"},{"name":"Azure ML","native":true,"category":"platform"},{"name":"AWS SageMaker","native":true,"category":"platform"},{"name":"Docker","native":true,"category":"platform"}]` | `[{"name":"PyTorch"},{"name":"TensorFlow"},{"name":"AIBrix"},{"name":"AReaL"},{"name":"Cosmos Curate"},{"name":"Daft"},{"name":"Data-Juicer"},{"name":"DeltaCAT"},{"name":"Modin"},{"name":"NeMo Curator"},{"name":"NeMo-RL"},{"name":"OpenRLHF"},{"name":"RayDP"},{"name":"ROLL"},{"name":"SkyRL"},{"name":"SLIME"},{"name":"Syftr"},{"name":"verl"},{"name":"vLLM"},{"name":"Kubernetes","native":true,"category":"infrastructure"},{"name":"AWS","native":true,"category":"cloud"},{"name":"GCP","native":true,"category":"cloud"},{"name":"Azure","native":true,"category":"cloud"},{"name":"Databricks","native":true,"category":"data_platform"},{"name":"DeltaLake","native":true,"category":"data_storage"},{"name":"Spark","native":true,"category":"data_processing","direction":"bidirectional"},{"name":"Pandas","native":true,"category":"data_processing","direction":"bidirectional"}]` |
| language.primary | Python | Python |
| license.spdx | Apache-2.0 | Apache-2.0 |
| platform.support | `{"cli":true,"web":true}` | `{"cli":true}` |
| pricing | `{"type":"open_source","sourceUrl":"https://mlflow.org","retrievedAt":"2026-10-05T10:15:00.395Z"}` | `{"type":"open_source","sourceUrl":"https://www.ray.io","retrievedAt":"2026-09-14T15:30:52.746Z"}` |
| pricing.free_tier | yes | yes |
| pricing.model | open_source | commercial |
| pricing.price_level | free | free |
| pricing.transparent | yes | - |
| release.cadence_days | 9 | 18 |
| release.history | `[{"url":"https://github.com/mlflow/mlflow/releases/tag/model-catalog/latest","date":"2026-04-06T05:49:14Z","type":"stable","version":"model-catalog/latest"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v2.11.5","date":"2026-09-23T06:17:56Z","type":"stable","version":"v2.11.5"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.16.1","date":"2026-09-17T02:40:08Z","type":"stable","version":"v3.16.1"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.16.0","date":"2026-09-04T08:30:54Z","type":"stable","version":"v3.16.0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.15.2","date":"2026-08-26T08:34:31Z","type":"stable","version":"v3.15.2"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.15.1","date":"2026-08-03T11:09:58Z","type":"stable","version":"v3.15.1"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.15.0","date":"2026-07-31T08:59:13Z","type":"stable","version":"v3.15.0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.14.0","date":"2026-06-17T08:50:33Z","type":"stable","version":"v3.14.0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.13.0","date":"2026-06-01T23:24:24Z","type":"stable","version":"v3.13.0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.13.0rc0","date":"2026-05-22T07:41:13Z","type":"prerelease","version":"v3.13.0rc0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/ts/v0.2.0","date":"2026-05-15T04:09:03Z","type":"stable","version":"ts/v0.2.0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.12.0","date":"2026-05-05T23:48:58Z","type":"stable","version":"v3.12.0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.12.0rc0","date":"2026-04-28T23:25:56Z","type":"prerelease","version":"v3.12.0rc0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/ts/v0.2.0-rc.1","date":"2026-04-13T09:42:04Z","type":"prerelease","version":"ts/v0.2.0-rc.1"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.11.1","date":"2026-04-08T05:29:25Z","type":"stable","version":"v3.11.1"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.11.0rc1","date":"2026-04-01T09:14:13Z","type":"prerelease","version":"v3.11.0rc1"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.11.0rc0","date":"2026-03-16T14:02:42Z","type":"prerelease","version":"v3.11.0rc0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.10.1","date":"2026-03-05T14:47:14Z","type":"stable","version":"v3.10.1"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.10.0","date":"2026-02-20T16:05:05Z","type":"stable","version":"v3.10.0"},{"url":"https://github.com/mlflow/mlflow/releases/tag/v3.10.0rc0","date":"2026-02-12T05:01:00Z","type":"prerelease","version":"v3.10.0rc0"}]` | `[{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.59.0","date":"2026-10-02T07:04:37Z","type":"stable","version":"ray-2.59.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.58.0","date":"2026-08-23T05:42:08Z","type":"stable","version":"ray-2.58.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.57.0","date":"2026-08-11T01:15:44Z","type":"stable","version":"ray-2.57.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.56.1","date":"2026-07-17T23:19:47Z","type":"stable","version":"ray-2.56.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.56.0","date":"2026-06-29T20:32:55Z","type":"stable","version":"ray-2.56.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.55.1","date":"2026-04-22T20:24:41Z","type":"stable","version":"ray-2.55.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.55.0","date":"2026-04-15T20:34:27Z","type":"stable","version":"ray-2.55.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.54.1","date":"2026-03-25T23:37:39Z","type":"stable","version":"ray-2.54.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.54.0","date":"2026-02-18T23:44:44Z","type":"stable","version":"ray-2.54.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.53.0","date":"2025-12-20T15:16:24Z","type":"stable","version":"ray-2.53.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.51.2","date":"2025-11-29T00:40:40Z","type":"stable","version":"ray-2.51.2"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.52.1","date":"2025-11-28T02:23:22Z","type":"stable","version":"ray-2.52.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.52.0","date":"2025-11-21T19:10:39Z","type":"stable","version":"ray-2.52.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.51.1","date":"2025-11-01T03:27:11Z","type":"stable","version":"ray-2.51.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.51.0","date":"2025-10-29T05:33:49Z","type":"stable","version":"ray-2.51.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.50.1","date":"2025-10-18T19:21:43Z","type":"stable","version":"ray-2.50.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.50.0","date":"2025-10-10T23:06:29Z","type":"stable","version":"ray-2.50.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.49.2","date":"2025-09-19T18:10:36Z","type":"stable","version":"ray-2.49.2"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.49.1","date":"2025-09-03T00:44:11Z","type":"stable","version":"ray-2.49.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.49.0","date":"2025-08-26T19:52:24Z","type":"stable","version":"ray-2.49.0"}]` |
| reliability.status_page | - | yes |
| security.scorecard | 5.4 | 5.7 |
| security.trust_center | https://mlflow.org/articles/tags/ai-compliance-policies/ | - |
| security.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"}` |

## Capabilities (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 | - | - |

*Source: vioscaleAI. Generated 2026-10-16T08:18:54.011Z. "-" = undocumented, not absent.*