Hatchet logo
vs
Trigger.dev logo

Hatchet vs Trigger.dev

A side-by-side comparison of Hatchet and Trigger.dev across 26 workflow orchestration capabilities. Hatchet fully supports 18 of them and Trigger.dev fully supports 17; of the 12 mandatory features, Hatchet covers 10 and Trigger.dev covers 10.

Hatchet

Hatchet is an open-source, Postgres-based platform for running background tasks, durable workflows and AI agents at scale, with SDKs for Python, TypeScript and Go.

Features fully supported18 / 26
Mandatory features: 10 / 12View profile

Trigger.dev

Trigger.dev is an open-source platform for building and running durable background tasks, cron jobs and AI agent workflows in TypeScript, with retries, queues and full observability.

Features fully supported17 / 26
Mandatory features: 10 / 12View profile

Feature comparison

9 of 26 capabilities differ between Hatchet and Trigger.dev.

Change tools
CapabilityHatchetTrigger.dev
DAG-based workflow definition
Define dependencies and execution order
Mandatory
YesPartial
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
YesYes
Task retries
Handle transient failures
Mandatory
YesYes
Retry policies (backoff, limits)
Avoid cascading failures
Recommended
YesYes
Scheduling (cron / time-based)
Automated recurring workflows
Depends
YesYes
Event-driven execution
React to external systems
Depends
YesPartial
Backfills / replays
Reprocess historical data
Depends
PartialPartial
Idempotency support
Safe retries & replays
Mandatory
PartialYes
Exactly-once semantics
Correctness for business workflows
Optional
NoPartial
Long-running workflows (days/months)
Business processes, approvals
Depends
YesYes
Human-in-the-loop steps
Approvals, manual actions
Optional
YesYes
Dynamic workflows at runtime
Conditional execution
Depends
YesYes
Workflow versioning
Safe evolution over time
Recommended
PartialYes
Distributed execution
Scalability
Mandatory
YesYes
High availability scheduler
Production reliability
Recommended
PartialPartial
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
YesYes
Native Kubernetes support
Modern infra compatibility
Depends
YesYes
Multi-language SDKs
Polyglot systems
Optional
YesNo
Deterministic replay
Safe recovery & correctness
Optional
PartialNo
Pluggable execution backends
Flexibility
Recommended
NoPartial

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