Automation Integration · head to head
Flowise vs Hatchet

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: Flowise enterprise tier requires custom pricing with no published rates; 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 Flowise and Hatchet actually diverge.
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 Flowise
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.
Flowise
- Building multi-agent systems with orchestrated workflowsnot Hatchet
- Creating chatbots that retrieve knowledge from uploaded documentsnot Hatchet
- Implementing human-in-the-loop approval for AI agent decisionsnot Hatchet
- Deploying conversational AI without writing backend codenot Hatchet
Hatchet
- An AI product running long agent pipelines that must survive worker restarts and resume mid-workflownot Flowise
- A team that outgrew Celery and wants concurrency keys, fairness and rate limiting without building themnot Flowise
- An engineering group that wants durable execution self-hosted with no datastore beyond the Postgres they already runnot Flowise
- A multi-tenant SaaS that needs one noisy customer's jobs not to starve everyone else'snot Flowise
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Flowise
- Enterprise tier requires custom pricing with no published rates
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
Flowise
Free- FreeFree
- 2 Flows & Assistants
- 100 predictions per month
- 5 MB storage
- Starter$35/month
- Unlimited flows & assistants
- 10,000 predictions per month
- 1 GB storage
- Pro$65/month
- 50,000 predictions per month
- 10 GB storage
- Unlimited workspaces
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 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 Flowise or Hatchet better?
- Neither clearly leads. Flowise 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, Flowise or Hatchet?
- Flowise starts at Free and Hatchet at Free.
- Does Flowise or Hatchet run on more platforms?
- Flowise runs on Web. Hatchet runs on Linux, Docker, Kubernetes, Cloud.
- Can I use Flowise for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Flowise best used for?
- Flowise is most often used for building multi-agent systems with orchestrated workflows, creating chatbots that retrieve knowledge from uploaded documents, implementing human-in-the-loop approval for ai agent decisions, deploying conversational ai without writing backend code. Of those, building multi-agent systems with orchestrated workflows and creating chatbots that retrieve knowledge from uploaded documents are not what Hatchet is typically brought in for.
- What can Flowise do that Hatchet cannot?
- Hatchet covers Postgres-backed queue, Durable execution, DAG workflows, Concurrency and fairness.
Answered from the vendors’ own pages
Flowise: Does Flowise have a free tier?
Yes, Flowise offers a free plan with 2 flows and assistants, 100 predictions per month, 5 MB storage, and community support.
SourceHatchet: Is Hatchet open source?
Yes, the engine is MIT licensed and can be self-hosted, with a managed cloud offered alongside.
Flowise: What is Flowise's Starter plan pricing?
The Starter plan costs $35 per month (first month free) and includes unlimited flows and assistants, 10,000 predictions per month, and 1 GB storage.
SourceHatchet: 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.
Flowise: How does Flowise charge for additional users?
Additional users on the Pro plan cost $15 per user per month. The Pro plan supports 5+ users with this per-user add-on pricing.
SourceHatchet: 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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