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Luigi vs Mage

A side-by-side comparison of Luigi and Mage across 26 workflow orchestration capabilities. Luigi fully supports 7 of them and Mage fully supports 14; of the 12 mandatory features, Luigi covers 6 and Mage covers 7.

Luigi

Luigi is an open-source Python package from Spotify for building complex pipelines of batch jobs, handling dependency resolution, workflow management and visualization.

Features fully supported7 / 26
Mandatory features: 6 / 12View profile

Mage

Mage is an open-source data pipeline tool for transforming and integrating data, combining a notebook-style editor with modular, testable code blocks in Python, SQL and R.

Features fully supported14 / 26
Mandatory features: 7 / 12View profile

Feature comparison

17 of 26 capabilities differ between Luigi and Mage.

Change tools
CapabilityLuigiMage
DAG-based workflow definition
Define dependencies and execution order
Mandatory		YesYes
Code-first workflows
Versionable, testable workflows
Mandatory		YesYes
Declarative workflow model
Predictability, reproducibility
Mandatory		NoPartial
Task dependency resolution
Correct execution order
Mandatory		YesYes
Persistent workflow state
Crash recovery, observability
Mandatory		PartialYes
Task retries
Handle transient failures
Mandatory		YesYes
Retry policies (backoff, limits)
Avoid cascading failures
Recommended		NoYes
Scheduling (cron / time-based)
Automated recurring workflows
Depends		YesYes
Event-driven execution
React to external systems
Depends		NoYes
Backfills / replays
Reprocess historical data
Depends		NoYes
Idempotency support
Safe retries & replays
Mandatory		NoPartial
Exactly-once semantics
Correctness for business workflows
Optional		NoNo
Long-running workflows (days/months)
Business processes, approvals
Depends		NoNo
Human-in-the-loop steps
Approvals, manual actions
Optional		NoNo
Dynamic workflows at runtime
Conditional execution
Depends		NoYes
Workflow versioning
Safe evolution over time
Recommended		NoPartial
Distributed execution
Scalability
Mandatory		YesPartial
High availability scheduler
Production reliability
Recommended		NoPartial
Fault-tolerant execution
Crash safety
Mandatory		NoPartial
Observability (logs, states, UI)
Debugging & ops
Mandatory		PartialYes
Workflow-level visibility
Understand end-to-end runs
Mandatory		PartialYes
Task isolation
Failure containment
Mandatory		YesPartial
Native Kubernetes support
Modern infra compatibility
Depends		NoYes
Multi-language SDKs
Polyglot systems
Optional		NoPartial
Deterministic replay
Safe recovery & correctness
Optional		NoNo
Pluggable execution backends
Flexibility
Recommended		NoYes

* To be considered a complete workflow orchestration tool, a tool must implement the features marked as mandatory according to our assessment.

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Learn more

Read the full profiles, including pros and cons, installation and alternatives.

LuigiMage

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