FlowHub
Apache DolphinScheduler logo
vs
Luigi logo

Apache DolphinScheduler vs Luigi

A side-by-side comparison of Apache DolphinScheduler and Luigi across 26 workflow orchestration capabilities. Apache DolphinScheduler fully supports 14 of them and Luigi fully supports 7; of the 12 mandatory features, Apache DolphinScheduler covers 9 and Luigi covers 6.

Apache DolphinScheduler

Apache DolphinScheduler is a distributed, extensible data orchestration platform with a visual DAG editor for building, scheduling and monitoring batch and data workflows.

Features fully supported14 / 26
Mandatory features: 9 / 12View profile

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

Feature comparison

17 of 26 capabilities differ between Apache DolphinScheduler and Luigi.

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

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

Spotted an inaccuracy? contact@workflows.guru

Learn more

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

Apache DolphinSchedulerLuigi

Related comparisons