# Arize AI vs Ray

| Attribute | Arize AI | Ray |
|---|---|---|
| **Vioscale score** | 70.5 (32% (low)) | 66.8 (68% (medium)) |
| activity.commits_last_30d | - | 100 |
| adoption.dependent_repos | - | 3,641 |
| adoption.github_stars | - | 43,612 |
| adoption.package_downloads_weekly | - | 11,291,327 |
| deployment.options | `{"cloud":true,"on_prem":true,"self_hosted":true}` | `{"cloud":true,"hybrid":true,"on_prem":true,"self_hosted":true}` |
| description.long | An AI engineering platform that enables teams to observe agent behavior end-to-end, run evaluations at scale, and systematically improve agents through testing and experimentation, available as both a managed cloud service and self-hosted deployment. | 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. |
| features.capabilities | `{"role":"platform","evaluation":true,"managed_cloud":true,"self_hostable":true,"multi_provider":true,"vpc_deployment":true,"otel_compatible":true,"llm_observability":true,"prompt_management":true,"framework_agnostic":true,"experiment_tracking":true}` | `{"managed_cloud":true,"model_serving":true,"self_hostable":true,"multi_provider":true,"vpc_deployment":true,"framework_agnostic":true,"experiment_tracking":true}` |
| integrations.count | 25 | 17 |
| integrations.list | `[{"name":"OpenAI"},{"name":"Anthropic"},{"name":"Azure OpenAI"},{"name":"AWS Bedrock"},{"name":"Vertex AI"},{"name":"Google GenAI"},{"name":"NVIDIA NIM"},{"name":"Gemini"},{"name":"OpenRouter"},{"name":"LiteLLM"},{"name":"Claude Code"},{"name":"Cursor"},{"name":"OpenCode"},{"name":"LangGraph"},{"name":"Vercel AI SDK"},{"name":"Mastra"},{"name":"CrewAI"},{"name":"LlamaIndex"},{"name":"DSPy"},{"name":"OpenAI Agents SDK"},{"name":"Claude Agent SDK"},{"name":"BigQuery"},{"name":"Databricks"},{"name":"Snowflake"},{"name":"OpenTelemetry"}]` | `[{"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"}]` |
| language.primary | - | Python |
| license.spdx | - | Apache-2.0 |
| platform.support | `{"cli":true,"web":true}` | `{"cli":true}` |
| pricing | - | `{"type":"free","freeTier":true,"sourceUrl":"https://www.ray.io","retrievedAt":"2026-08-14T16:39:27.110Z"}` |
| pricing.free_tier | - | yes |
| pricing.model | commercial | commercial |
| pricing.price_level | - | free |
| release.cadence_days | - | 18 |
| release.history | - | `[{"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"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.48.0","date":"2025-07-18T22:27:25Z","type":"stable","version":"ray-2.48.0"}]` |
| reliability.status_page | yes | yes |
| security.gdpr | yes | - |
| security.hipaa | yes | - |
| security.iso27001 | yes | - |
| security.pci | yes | - |
| security.scorecard | - | 5.7 |
| security.soc2 | yes | - |
| security.vulnerabilities | - | `{"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 | Arize AI | Ray |
|---|:--:|:--:|
| **Core** |  |  |
| Tool role | End-to-end ML platform | - |
| **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: Vioscale. Generated 2026-09-01T14:30:50.995Z. "-" = undocumented, not absent.*