n8n vs Make
Side-by-side comparison to help you choose the right tool for your business
Our Verdict: n8n for technical teams and cost control, Make for visual workflow design
Make's visual scenario builder is the most intuitive in the automation space, it thinks in data flows rather than linear steps, which makes complex routing feel natural. n8n matches this visual power but adds self-hosting and full code access. If your team has a developer, n8n saves money and gives more control. If your team is non-technical but needs sophisticated logic, Make's visual approach is hard to beat.
Our Implementation Experience
Both are excellent. Make is our recommendation when the client wants a managed cloud solution with no DevOps overhead. n8n when they want maximum control, self-hosting for data sovereignty (healthcare clients especially), or need the native AI agent capabilities. Make's visual builder is genuinely better for non-linear workflows with lots of conditional branches.
Based on real client deployments, not spec sheet comparisons.
At a Glance
Developer-friendly teams that want open-source automation
Free (self-hosted) / $24/mo (Starter) / $60/mo (Pro) / Custom (Enterprise)
intermediate
3-7 days
Teams that want powerful visual automation without writing code
Free (1,000 credits) / $9/mo (Core) / $16/mo (Pro) / $29/mo (Teams), annual billing at 10k credits/mo; $10.59/$18.82/$34.12 monthly, read 2026-10-11 / Custom (Enterprise)
intermediate
2-5 days
Feature Comparison
| Feature | n8n | Make |
|---|---|---|
| Self-hosting | Yes (Docker, npm) | No |
| Visual builder | Good (flowchart-style) | Excellent (data-flow style) |
| Custom code | Full JavaScript + Python | Limited (single function) |
| Data transformation | Code nodes + expressions | Built-in visual mapper |
| Error handling | Try/catch workflows | Break + retry + rollback |
| Version control | Git integration | Scenario history only |
| Scheduling | Cron expressions (flexible) | Interval-based + cron |
| AI/LLM support | Native LangChain + vector stores | OpenAI + basic AI modules |
Which to Choose by Use Case
Agency managing 20 client automations
Self-host once, run unlimited client workflows. Make would cost $200+/month in operations fees across all clients.
Marketing team building a lead scoring pipeline
Visual data mapper makes it easy to transform CRM fields, apply scoring logic, and route leads, all without code.
SaaS company syncing data between 5 internal tools
Custom JavaScript nodes handle the edge cases (data format differences, retry logic, deduplication) that Make's visual tools struggle with.
E-commerce store automating order fulfillment
Pre-built Shopify, ShipStation, and accounting app modules with deep field mapping. Works out of the box without developer involvement.
Need Help Deciding?
We implement both options. Tell us your use case and we'll recommend the right fit, then set it up for you.
Frequently Asked Questions
Is Make the same as Integromat?
Yes: Integromat rebranded to Make in early 2022. The platform is the same, with a refreshed UI and expanded features. If you used Integromat, Make will feel familiar with improvements to the visual builder and pricing model.
Which is cheaper for high-volume automation?
n8n self-hosted is unbeatable: $5-10/month for a VPS regardless of execution count. Make's credit-based pricing rises in tiers: 50,000 operations/month needs its 80,000-credit tier, $55/mo Core or $91/mo Pro on annual billing ($64.71/$107.06 monthly, read 2026-10-11). n8n cloud is similarly priced at that scale, but self-hosted is nearly free.
Can Make handle complex branching workflows?
Yes: Make's router module handles multiple branches with filters, and its visual approach makes complex flows easier to understand than most tools. However, for deeply nested conditional logic (5+ levels), n8n's code nodes are more maintainable.
Which has better AI workflow support?
n8n, significantly. Its native LangChain integration supports agents, vector stores, memory, and tool calling. Make has OpenAI modules and basic AI features, but lacks the depth for building sophisticated AI workflows like RAG pipelines or multi-agent systems.
Related Comparisons
More head-to-head matchups for the tools in this comparison
n8n vs Zapier vs Make
n8n for power users, Zapier for simplicity, Make for visual builders
n8n vs LangChain
n8n for business automation, LangChain for custom AI agent development
n8n vs Zapier
n8n for power users and cost control, Zapier for speed and simplicity
Zapier vs Make
Zapier for simplicity, Make for complex visual workflows
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