
Dagster vs Hatchet
A side-by-side comparison of Dagster and Hatchet across 26 workflow orchestration capabilities. Dagster fully supports 12 of them and Hatchet fully supports 18; of the 12 mandatory features, Dagster covers 10 and Hatchet covers 10.
Dagster
Dagster is an open-source data orchestration platform that helps you build, deploy, and observe data pipelines and data assets.
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.
Feature comparison
12 of 26 capabilities differ between Dagster and Hatchet.
| Capability | Importance* | ||
|---|---|---|---|
DAG-based workflow definition Define dependencies and execution order Mandatory | Mandatory | Yes | Yes |
Code-first workflows Versionable, testable workflows Mandatory | Mandatory | Yes | Yes |
Declarative workflow model Predictability, reproducibility Mandatory | Mandatory | Yes | Partial |
Task dependency resolution Correct execution order Mandatory | Mandatory | Yes | Yes |
Persistent workflow state Crash recovery, observability Mandatory | Mandatory | Yes | Yes |
Task retries Handle transient failures Mandatory | Mandatory | Yes | Yes |
Retry policies (backoff, limits) Avoid cascading failures Recommended | Recommended | Yes | Yes |
Scheduling (cron / time-based) Automated recurring workflows Depends | Depends | Partial | Yes |
Event-driven execution React to external systems Depends | Depends | Partial | Yes |
Backfills / replays Reprocess historical data Depends | Depends | Partial | Partial |
Idempotency support Safe retries & replays Mandatory | Mandatory | Partial | Partial |
Exactly-once semantics Correctness for business workflows Optional | Optional | Yes | No |
Long-running workflows (days/months) Business processes, approvals Depends | Depends | Partial | Yes |
Human-in-the-loop steps Approvals, manual actions Optional | Optional | No | Yes |
Dynamic workflows at runtime Conditional execution Depends | Depends | Partial | Yes |
Workflow versioning Safe evolution over time Recommended | Recommended | Partial | Partial |
Distributed execution Scalability Mandatory | Mandatory | Yes | Yes |
High availability scheduler Production reliability Recommended | Recommended | Partial | Partial |
Fault-tolerant execution Crash safety Mandatory | Mandatory | Partial | Yes |
Observability (logs, states, UI) Debugging & ops Mandatory | Mandatory | Yes | Yes |
Workflow-level visibility Understand end-to-end runs Mandatory | Mandatory | Yes | Yes |
Task isolation Failure containment Mandatory | Mandatory | Yes | Yes |
Native Kubernetes support Modern infra compatibility Depends | Depends | Partial | Yes |
Multi-language SDKs Polyglot systems Optional | Optional | No | Yes |
Deterministic replay Safe recovery & correctness Optional | Optional | No | Partial |
Pluggable execution backends Flexibility Recommended | Recommended | Partial | No |
* 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.
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