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Automation Integration · head to head

Dagster vs Hatchet

Dagster logo

Dagster

Automation Integration

Data orchestration platform with asset lineage and AI-native observability

From
Free
Rated
-
Hatchet logo

Hatchet

Automation Integration

Postgres-backed distributed task queue and workflow engine for Python, TypeScript and Go

From
Free
Rated
-

The short version

  • Each has a real cost: Dagster learning curve steeper than simpler task schedulers; Hatchet postgres as the queue backend simplifies operations but sets a throughput ceiling, and very high task rates require database tuning or partitioning work that a purpose-built queue would not demand.
  • They diverge on capability: Dagster covers Asset-centric orchestration, Hatchet covers Postgres-backed queue.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Dagster and Hatchet actually diverge.

Attributes where Dagster and Hatchet differ
AttributeDagsterHatchet
Pricing modelFree open-source core plus paid cloud platformPer month by task run count
PlatformsCloud, Self-hostedLinux, Docker, Kubernetes, Cloud

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Automation Integration).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Dagster

  • Asset-centric orchestration
  • Lineage tracking
  • Data quality monitoring
  • Multi-tool integration
  • Branch deployments
  • Dagster+ AI
  • Hybrid deployment

Only in Hatchet

  • Postgres-backed queue
  • Durable execution
  • DAG workflows
  • Concurrency and fairness
  • Rate limiting
  • Cron and scheduling
  • Multi-language SDKs
  • Self-hosting

What people use each for

The jobs each tool is most often brought in to do.

Dagster

  • Orchestrating multi-stage data transformation pipelinesnot Hatchet
  • Tracking data lineage across transformation toolsnot Hatchet
  • Monitoring data quality and asset healthnot Hatchet
  • Coordinating dbt and Snowflake workflowsnot Hatchet

Hatchet

  • An AI product running long agent pipelines that must survive worker restarts and resume mid-workflownot Dagster
  • A team that outgrew Celery and wants concurrency keys, fairness and rate limiting without building themnot Dagster
  • An engineering group that wants durable execution self-hosted with no datastore beyond the Postgres they already runnot Dagster
  • A multi-tenant SaaS that needs one noisy customer's jobs not to starve everyone else'snot Dagster

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Dagster

  • Learning curve steeper than simpler task schedulers
  • Asset-centric model requires redesigning existing task-based pipelines
  • Pricing complex with per-credit costs on top of base fee
  • Open-source version requires self-hosting infrastructure
  • Limited to data workflows; not suitable for general automation

Hatchet

  • Postgres as the queue backend simplifies operations but sets a throughput ceiling, and very high task rates require database tuning or partitioning work that a purpose-built queue would not demand.
  • Data retention on the managed tiers is three days on Team and seven on Scale, which is short for debugging intermittent failures and forces you to export run history elsewhere.
  • The step from the free tier to Team is 500 US dollars a month plus usage, which is a large increment for a small team that simply needs a production SLA.
  • Hatchet is a young company in a category with Temporal, Inngest and cloud-native alternatives already established, so ecosystem, hiring pool and third-party material are all thin.
  • Self-hosting the MIT engine is realistic but you then run the engine, its Postgres and its workers yourself, and the managed features such as audit logs and support are not part of that.

Pricing, plan by plan

Dagster

Free
  • Open SourceFree
    • Self-hosted deployment
    • Full orchestration engine
    • Community support
  • Solo$10/month
    • 1 user and 1 code location
    • Pay-as-you-go credits at $0.040 per credit
    • 1 deployment
  • Starter$100/month
    • Up to 3 users and 5 code locations
    • Better credit rate at $0.035 per credit
    • 1 deployment
  • Pro$null/custom
    • Unlimited code locations and deployments
    • Custom serverless compute pricing
    • Personalized onboarding

Hatchet

Free
  • DeveloperFree
    • First 100,000 task runs included
    • $10 per million task runs after
    • No card required
  • Team$500/month
    • Usage billed on top of the base fee
    • 10 users and 5 tenants
    • 3 day data retention
  • Scale$1000/month
    • Unlimited users and tenants
    • 7 day data retention
    • Audit logs
  • Enterprise$undefined/year
    • 300 million plus runs a month
    • Latency guarantees and custom SLAs
    • SSO and audit logging

Which should you pick?

Choose Dagster if

  • You need asset-centric orchestration.
  • You want to start without paying.
  • You work on Cloud, Self-hosted.
  • You also want lineage tracking.

Choose Hatchet if

  • You need postgres-backed queue.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Cloud.
  • You also want durable execution.

Questions people ask

Is Dagster or Hatchet better?
Neither clearly leads. Dagster starts at Free and Hatchet at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dagster or Hatchet?
Dagster starts at Free and Hatchet at Free.
Does Dagster or Hatchet run on more platforms?
Dagster runs on Cloud, Self-hosted. Hatchet runs on Linux, Docker, Kubernetes, Cloud.
Can I use Dagster for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dagster best used for?
Dagster is most often used for orchestrating multi-stage data transformation pipelines, tracking data lineage across transformation tools, monitoring data quality and asset health, coordinating dbt and snowflake workflows. Of those, orchestrating multi-stage data transformation pipelines and tracking data lineage across transformation tools are not what Hatchet is typically brought in for.
What can Dagster do that Hatchet cannot?
Dagster covers Asset-centric orchestration, Lineage tracking, Data quality monitoring, Multi-tool integration. Hatchet covers Postgres-backed queue, Durable execution, DAG workflows, Concurrency and fairness.

Answered from the vendors’ own pages

Dagster: What does Solo plan at $10/month include?

Solo includes 1 user, 1 code location, 1 deployment, and serverless compute at $0.010/minute, with 30-day free trial.

Source
Hatchet: Is Hatchet open source?

Yes, the engine is MIT licensed and can be self-hosted, with a managed cloud offered alongside.

Dagster: How are credits calculated on Dagster+?

Each asset materialization and ops execution costs 1 credit. Solo plan charges $0.040 per credit; Starter reduces to $0.035 per credit.

Source
Hatchet: What does it cost?

Free for the first 100,000 task runs, then 10 US dollars per million. Team is 500 US dollars a month plus usage; Scale is 1,000.

Dagster: Is Dagster open-source available for free?

Yes, Dagster open-source is free and includes the full orchestration engine for self-hosted deployment with community support.

Source
Hatchet: Why Postgres as the queue?

So durable task state lives in a database your team already backs up, replicates and can inspect with SQL, instead of a second system.

Hatchet: How does it compare with Temporal?

Lighter to adopt and operate, with a much smaller ecosystem and a lower throughput ceiling from the Postgres backend.

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