ray-project/ray Graph

Graph Summary

ray-project/ray graph connects 3 alternatives, 8 related projects, 1 inferred dependencies, 5 deployment targets, and 3 use cases.

Nodes68

Edges410

Projects50

Dependencies23

Open project knowledge Find alternatives Explore related projects Explain score Compare shortlist

Alternatives3 linked signals Related8 linked signals Dependencies1 linked signals Deployments5 linked signals Use Cases3 linked signals Categories28 linked signals Migrations3 linked signals

Project Context

ray

Maintainerray-project

LicenseApache-2.0

LanguagePython

Recent activityActive in the last week

Deployment Targets

Dependencies

Knowledge Graph

68 nodes / 410 edges

ray-project/ray ↔ Unstructured-IO/unstructuredUse Unstructured-IO/unstructured when the user needs a workflow automation project with docker, library-only, local deployment options.

ray-project/ray ↔ PrefectHQ/prefectUse PrefectHQ/prefect when the user needs a workflow automation project with docker, library-only, local deployment options.

ray-project/ray ↔ langflow-ai/langflowUse langflow-ai/langflow when the user needs a workflow automation project with docker, library-only, local deployment options.

ray-project/ray ↔ windmill-labs/windmillUse windmill-labs/windmill when the user needs a workflow automation project with docker, kubernetes, library-only deployment options.

ray-project/ray ↔ langgenius/difyUse langgenius/dify when the user needs a workflow automation project with docker, local, cloud deployment options.

ray-project/ray ↔ smithersai/smithersUse smithersai/smithers when the user needs a workflow automation project with docker, library-only, local deployment options.

Alternatives Network

Replacement candidates

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ray-project/ray ↔ openai/openai-agents-pythonUse openai/openai-agents-python when the user needs a workflow automation project with docker, library-only, local deployment options.

ray-project/ray ↔ apache/airflowUse apache/airflow when the user needs a workflow automation project with docker, kubernetes, library-only deployment options.

ray-project/ray ↔ Skyvern-AI/skyvernUse Skyvern-AI/skyvern when the user needs a workflow automation project with docker, library-only, local deployment options.

ray-project/ray ↔ langflow-ai/langflowUse langflow-ai/langflow when the user needs a workflow automation project with docker, library-only, local deployment options.

ray-project/ray ↔ microsoft/agent-frameworkUse microsoft/agent-framework when the user needs a workflow automation project with library-only, local, cloud deployment options.

ray-project/ray ↔ langgenius/difyUse langgenius/dify when the user needs a workflow automation project with docker, local, cloud deployment options.

Migration Paths

What to verify before switching

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These paths are evidence-backed heuristics, not drop-in compatibility claims.

ray-project/ray -> openai/openai-agents-pythonCompatibility: high / estimated cost: medium.Shared: category:workflow_automation, deployment:docker, deployment:library_only, deployment:local, deployment:cloud, use_case:orchestrate AI workflows, use_case:connect tools and services, use_case:automate repeated tasks.Gaps: Deployment targets not listed by target: kubernetes. License changes from Apache-2.0 to MIT.Validate: Review license obligations before migrating production code. Compare API, configuration, license, and dependency requirements. Run the target project's minimal example or test suite. Verify deployment, persistence, and tool-execution behavior in the requested runtime.

ray-project/ray -> apache/airflowCompatibility: high / estimated cost: low.Shared: category:workflow_automation, deployment:docker, deployment:kubernetes, deployment:library_only, deployment:local, deployment:cloud, use_case:orchestrate AI workflows, use_case:connect tools and services.Gaps: No indexed gap; still run the validation steps.Validate: Compare API, configuration, license, and dependency requirements. Run the target project's minimal example or test suite. Verify deployment, persistence, and tool-execution behavior in the requested runtime.

ray-project/ray -> Skyvern-AI/skyvernCompatibility: high / estimated cost: medium.Shared: category:workflow_automation, deployment:docker, deployment:library_only, deployment:local, deployment:cloud, use_case:orchestrate AI workflows, use_case:connect tools and services, use_case:automate repeated tasks.Gaps: Deployment targets not listed by target: kubernetes. License changes from Apache-2.0 to AGPL-3.0.Validate: Review license obligations before migrating production code. Compare API, configuration, license, and dependency requirements. Run the target project's minimal example or test suite. Verify deployment, persistence, and tool-execution behavior in the requested runtime.

Use Cases