dagster-io/dagster Graph

Graph Summary

dagster-io/dagster graph connects 3 alternatives, 8 related projects, 0 inferred dependencies, 4 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 Dependencies0 linked signals Deployments4 linked signals Use Cases3 linked signals Categories28 linked signals Migrations3 linked signals

Project Context

dagster

Maintainerdagster-io

LicenseApache-2.0

LanguagePython

Recent activityActive in the last week

Deployment Targets

Dependencies

Knowledge Graph

68 nodes / 410 edges

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

dagster-io/dagster ↔ kestra-io/kestraUse kestra-io/kestra when the user needs a workflow automation project with docker, kubernetes, serverless deployment options.

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

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

dagster-io/dagster ↔ n8n-io/n8nUse n8n-io/n8n when the user needs a workflow automation project with docker, local, cloud deployment options.

dagster-io/dagster ↔ ray-project/rayUse ray-project/ray when the user needs a workflow automation project with docker, kubernetes, library-only deployment options.

Alternatives Network

Replacement candidates

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

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

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

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

dagster-io/dagster ↔ ray-project/rayUse ray-project/ray when the user needs a workflow automation project with docker, kubernetes, library-only deployment options.

dagster-io/dagster ↔ kestra-io/kestraUse kestra-io/kestra when the user needs a workflow automation project with docker, kubernetes, serverless deployment options.

Migration Paths

What to verify before switching

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

dagster-io/dagster -> microsoft/agent-frameworkCompatibility: high / estimated cost: medium.Shared: category:workflow_automation, deployment:library_only, deployment:local, deployment:cloud, use_case:orchestrate AI workflows, use_case:connect tools and services, use_case:automate repeated tasks, language:Python.Gaps: Deployment targets not listed by target: docker. 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.

dagster-io/dagster -> apache/airflowCompatibility: high / estimated cost: low.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: 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.

dagster-io/dagster -> PrefectHQ/prefectCompatibility: high / estimated cost: low.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: 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.

Use Cases