# Braintrust vs Ray

**Leader by Vioscale score:** Ray

| Attribute | Braintrust | Ray |
|---|---|---|
| **Vioscale score** | 57.9 (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,"hybrid":true,"on_prem":true}` | `{"cloud":true,"hybrid":true,"on_prem":true,"self_hosted":true}` |
| description.long | A platform for tracking AI agent performance at runtime, automatically discovering quality issues and behavioral patterns. Teams can run experiments, set quality expectations, and continuously improve agents through real-time trace inspection, evaluation scoring, and automated prompt optimization. | 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":"observability","evaluation":true,"soc2_type_ii":true,"managed_cloud":true,"model_serving":false,"self_hostable":true,"multi_provider":true,"vpc_deployment":true,"no_train_on_data":"unknown","llm_observability":true,"prompt_management":true,"architecture_model":"managed_cloud_saas","framework_agnostic":true,"experiment_tracking":true,"production_ab_testing_of_system_prompts":true,"token_cost_and_latency_waterfall_charts":true,"multi_step_agentic_workflow_distributed_tracing":true}` | `{"managed_cloud":true,"model_serving":true,"self_hostable":true,"multi_provider":true,"vpc_deployment":true,"framework_agnostic":true,"experiment_tracking":true}` |
| integrations.count | 3 | 17 |
| integrations.list | `[{"name":"OpenAI"},{"name":"Anthropic"},{"name":"Google"}]` | `[{"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 | `{"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 |
| 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.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 | Braintrust | Ray |
|---|:--:|:--:|
| **Core** |  |  |
| Tool role | LLM observability / eval | - |
| **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 | Unknown | - |

*Source: Vioscale. Generated 2026-09-01T14:40:04.103Z. "-" = undocumented, not absent.*