Apache DolphinScheduler logo
vs
Kestra logo

Apache DolphinScheduler vs Kestra

A side-by-side comparison of Apache DolphinScheduler and Kestra across 26 workflow orchestration capabilities. Apache DolphinScheduler fully supports 14 of them and Kestra fully supports 24; of the 12 mandatory features, Apache DolphinScheduler covers 9 and Kestra covers 11.

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

Kestra

Kestra is an open-source, event-driven orchestration platform that allows you to define, schedule, and monitor workflows declaratively in YAML, with support for both scheduled and real-time triggers.

Features fully supported24 / 26
Mandatory features: 11 / 12View profile

Feature comparison

12 of 26 capabilities differ between Apache DolphinScheduler and Kestra.

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

* 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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