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Automation Integration · head to head

Dify vs Hatchet

Dify logo

Dify

Automation Integration

The Platform for Production-Ready Agentic Workflows

From
Free
Rated
-
Full reviewWebsite
Hatchet logo

Hatchet

Automation Integration

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

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dify free tier limited to 200 monthly message credits; 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.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Dify and Hatchet actually diverge.

Attributes where Dify and Hatchet differ
AttributeDifyHatchet
Pricing modelfreemiumPer month by task run count
PlatformsWebLinux, 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 Dify

Nothing recorded that Hatchet does not also cover.

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.

Dify

  • AI workflow automationnot Hatchet
  • Custom application deploymentnot Hatchet

Hatchet

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

Where each one falls short

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

Dify

  • Free tier limited to 200 monthly message credits
  • Professional tier supports only 3 team members

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

Dify

Free
  • SandboxFree
    • 200 monthly message credits
    • 1 workspace
    • 5 apps
  • Professional$590/year
    • 5,000 monthly message credits
    • 3 team members
    • 50 apps
  • Team$1590/year
    • 10,000 monthly message credits
    • 50 team members
    • 200 apps

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 Dify if

  • You want to start without paying.
Dify review

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

Questions people ask

Is Dify or Hatchet better?
Neither clearly leads. Dify 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, Dify or Hatchet?
Dify starts at Free and Hatchet at Free.
Does Dify or Hatchet run on more platforms?
Dify runs on Web. Hatchet runs on Linux, Docker, Kubernetes, Cloud.
Can I use Dify for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dify best used for?
Dify is most often used for ai workflow automation, custom application deployment. Of those, ai workflow automation and custom application deployment are not what Hatchet is typically brought in for.
What can Dify do that Hatchet cannot?
Hatchet covers Postgres-backed queue, Durable execution, DAG workflows, Concurrency and fairness.

Answered from the vendors’ own pages

Dify: How much does Dify cost?

Dify Cloud offers a free Sandbox tier, Professional at $590/year with 5,000 monthly credits, and Team at $1,590/year with 10,000 monthly credits.

Source
Hatchet: Is Hatchet open source?

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

Dify: Is Dify free to use?

Yes, Dify offers a free Sandbox tier with 200 monthly message credits, 1 workspace, 5 apps, and 50MB storage. Community edition is free and open-source.

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.

Dify: What are Dify's team collaboration limits?

Professional tier supports 3 team members. Team tier supports 50 team members. Enterprise plans with custom team sizes require contacting sales.

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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