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Make vs n8n
A plain-English comparison to help you choose between them.
Pick Make for the polished hosted experience with deep visual logic and no infrastructure to run; pick n8n when self-hosting, code-level control and freedom from per-task economics matter more than polish. Make is the power tool you rent; n8n is the one you own.
Side by side
- Summary
Make is visual automation with engineering sensibilities: scenarios built on a canvas where branching, loops, error handling and data transformation are first-class, connecting thousands of apps at operation-level pricing that undercuts the per-task platforms at volume.
- Best for
- Branching, loops and error handling built visually
- High-volume automation at operation-level pricing
- Reusable AI agents inside scenarios, reasoning visible
- Data transformation between connected apps
- A visual map of the whole automation estate
- Less suited to
Per-operation billing still compounds: data-heavy scenarios that iterate over large sets consume operations quickly, and the arithmetic needs doing before scale. The cheapest at volume is still not cheap at extreme volume.
Its power also assumes a builder: teams wanting the absolute simplest trigger-action setup will move faster on the simpler platforms.
- Cost
- Free tier + paid plans
- Ease
- Intermediate
- Openness
- Hosted service
- Data
- Per Make's Help Center, "effective august 27th, 2025, we're replacing operations with credits as our billing unit," with existing operations converting 1:1. Standard modules stay at 1 credit, but native AI modules consume credits variably: per one 2026 review, "A workflow with AI Agents can consume 43-50 credits per execution (Small model), versus the few credits of a classic workflow." Extra credits cost 25% more than in-plan (Help Center, updated 6 Nov 2025), for both manual and auto-purchase. The sticker price is not the bill; consider calling AI APIs directly via HTTP for cost control.
- Summary
n8n is the engineer's automation platform: open source and self-hostable, with execution-based pricing that keeps high-volume workflows economical, visual nodes that accept real code when logic demands it, and first-class support for AI and agentic flows.
- Best for
- Self-hosted automation with data residency
- Execution-based pricing at high volume
- Visual flows with real code where needed
- AI and agentic workflows under your control
- Technical teams who want to own the platform
- Less suited to
Non-technical users face a real curve: the consumer platforms get simple automations running faster, and self-hosting adds operational effort that someone must own.
Its breadth of integrations, while large, also trails the biggest directory; the niche-app long tail sometimes lives elsewhere.
- Cost
- Free tier + paid plans
- Ease
- Advanced
- Openness
- Runs privately (self-hostable)
- Data
- Execution-based pricing (whole workflow = one execution) is usually cheaper than per-task, but AI Workflow Builder credits (50 Starter / 150 Pro) and any LLM API calls you wire in are metered separately, and Business overage is roughly €4,000 per 300,000 extra executions. The sticker price is not the whole bill. Self-hosting shifts cost to your own infrastructure/maintenance.
By area
Where each one pulls ahead, area by area.
| Area | Pick Make when | Pick n8n when |
|---|---|---|
| Automation & agents | Make is the polished hosted option | self-hosting and code-level control matter more than polish |
Common questions
Is self-hosting n8n actually hard?
For anyone comfortable with Docker and a small server, no: a working instance takes an evening. The real cost is ongoing ownership, including updates, backups and security, because an automation server holds credentials to everything it touches. Teams without a natural owner for that should honestly prefer hosted platforms.
Which handles complex logic better?
Both handle branching, iteration and error paths seriously. Make does it through a refined visual builder; n8n matches most of it visually and then goes further by letting you drop into real code when nodes run out of road. Pure visual sophistication favours Make; ultimate flexibility favours n8n.
What about data privacy?
Self-hosted n8n keeps workflow data and credentials entirely on your infrastructure, which is the strongest posture available and sometimes the deciding requirement. Make operates as a standard cloud platform under its commercial terms. If regulated data flows through your automations, that difference may make the decision for you.
Related comparisons
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Tool facts last checked July 2026