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Automation Integration · head to head

Hatchet vs Prefect

Hatchet logo

Hatchet

Automation Integration

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

From
Free
Rated
-
Full reviewWebsite
Prefect logo

Prefect

Automation Integration

Python-first workflow orchestration that heals itself

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Prefect limited to Python-based workflows; other languages require API calls
  • They diverge on capability: Hatchet covers Postgres-backed queue, Prefect covers Python function decorators.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Hatchet and Prefect actually diverge.

Attributes where Hatchet and Prefect differ
AttributeHatchetPrefect
Pricing modelPer month by task run countFreemium with per-user and usage-based tiers
PlatformsLinux, Docker, Kubernetes, CloudCloud, Self-hosted, VPC

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 Hatchet

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

Only in Prefect

  • Python function decorators
  • Automatic resilience
  • Flexible deployment
  • Observable execution
  • Multiple scheduling
  • Webhooks
  • Open-source core

What people use each for

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

Hatchet

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

Prefect

  • Orchestrating data pipeline workflows in Pythonnot Hatchet
  • Managing ML model training and inference jobsnot Hatchet
  • Building ETL and event-driven automationnot Hatchet
  • Monitoring and alerting on workflow healthnot Hatchet

Where each one falls short

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

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.

Prefect

  • Limited to Python-based workflows; other languages require API calls
  • Hobby free tier severely limited for production use
  • Team plan billing per user scales quickly with team size
  • Less visual workflow builder compared to some competitors
  • Smaller ecosystem of pre-built connectors than alternatives

Pricing, plan by plan

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

Prefect

Free
  • HobbyFree
    • 2 users and 5 deployments
    • 500 minutes serverless monthly
    • 7-day run retention
  • Starter$100/month
    • 3 users and 20 deployments
    • 75 hours serverless compute
    • Bring-your-own infrastructure
  • Team$100/user/month
    • 4-8 users per plan tier
    • 100 deployments
    • 225 hours serverless monthly
  • Enterprise$null/custom
    • SSO and SAML authentication
    • Role-based access control
    • Multiple workspaces

Which should you pick?

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.
Hatchet review

Choose Prefect if

  • You need python function decorators.
  • You want to start without paying.
  • You work on Cloud, Self-hosted, VPC.
  • You also want automatic resilience.
Prefect review

Questions people ask

Is Hatchet or Prefect better?
Neither clearly leads. Hatchet starts at Free and Prefect at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Hatchet or Prefect?
Hatchet starts at Free and Prefect at Free.
Does Hatchet or Prefect run on more platforms?
Hatchet runs on Linux, Docker, Kubernetes, Cloud. Prefect runs on Cloud, Self-hosted, VPC.
Can I use Hatchet for free?
Both have a free tier, so you can try either at no cost before committing.
What is Hatchet best used for?
Hatchet is most often used for an ai product running long agent pipelines that must survive worker restarts and resume mid-workflow, a team that outgrew celery and wants concurrency keys, fairness and rate limiting without building them, an engineering group that wants durable execution self-hosted with no datastore beyond the postgres they already run, a multi-tenant saas that needs one noisy customer's jobs not to starve everyone else's. Of those, an ai product running long agent pipelines that must survive worker restarts and resume mid-workflow and a team that outgrew celery and wants concurrency keys, fairness and rate limiting without building them are not what Prefect is typically brought in for.
What can Hatchet do that Prefect cannot?
Hatchet covers Postgres-backed queue, Durable execution, DAG workflows, Concurrency and fairness. Prefect covers Python function decorators, Automatic resilience, Flexible deployment, Observable execution.

Answered from the vendors’ own pages

Hatchet: Is Hatchet open source?

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

Prefect: What is included in the Hobby free plan?

Hobby includes 2 users, 5 deployments, 500 minutes of serverless compute monthly, and 7-day run retention.

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.

Prefect: What is the difference between Starter and Team plans?

Starter is $100/month for 3 users and 20 deployments. Team is $100 per user per month for 4-8 users and 100 deployments.

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.

Prefect: Can I deploy Prefect in my own infrastructure?

Yes, Starter and higher plans support bring-your-own-compute infrastructure and VPC deployments.

Source
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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