# n8n vs Make (2026): Which Automation Power Tool Should You Choose?

> n8n vs Make, compared honestly for 2026: two power tools weighed on pricing (per-execution + free self-host vs per-operation), catalog, visual polish, code, AI depth and data control. Which fits your team.

_Source: https://professionalstoolkit.com/articles/n8n-vs-make — The Professional's Toolkit · updated 2026-07-29_

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> **TL;DR —** n8n and Make are both *power* tools — node-based platforms for complex, branching automation, not simple "when-this-then-that" apps. The split is about ownership and code versus polish and catalog. **n8n** is self-hostable (free, unlimited executions), code-extensible (JavaScript/Python) and has the deeper AI-agent stack. **Make** is a hosted, exceptionally polished visual canvas with a larger app catalog and a gentler on-ramp for non-developers — billed on operations that scale with how elaborate your scenarios get. If you want ownership, code and AI depth, n8n wins; if you want the most refined visual builder and widest catalog with no infrastructure, Make wins.

## Two power tools, one real difference

Unlike the beginner-first tools, both n8n and Make embrace complexity: routers, branches, iterators, error handling, the works. So this comparison isn't "simple vs powerful" — both are powerful. The real difference is **ownership and extensibility versus polish and breadth**. n8n can run on your own servers and drop into real code; Make is hosted-only and no-code-first (with limited code steps), but its visual canvas is the most refined in the category and its catalog is far larger. Pick your axis and the choice follows.

## Head-to-head, at a glance

| Dimension | n8n | Make |
|---|---|---|
| Hosting | Self-host (free) or Cloud | Hosted-only |
| Pricing model | Per execution (whole run) · free self-hosted | Per operation (each module run) |
| App catalog | 400+ native (+ HTTP/code) | 3,000+ — broader |
| Visual polish | Functional, developer-oriented | Best-in-class visual canvas |
| Custom code | JavaScript & Python, first-class | Limited code modules |
| AI | Agent framework, RAG, your own model | Growing AI modules |
| Data control | Full — self-host keeps data in-house | Data flows through Make's cloud |
| Best for | Ownership, code, deep AI, cost at scale | Polished no-code branching, widest catalog |

## Pricing — different meters, and it matters

Both cost more than beginner tools for the depth they offer, but they meter differently.

- **Make** bills on **operations** — each module run inside a scenario consumes one. An elaborate scenario with iterators and many modules burns operations quickly, and an iterator over 200 items is 200 operations. Cost scales with how *elaborate* your scenarios are.
- **n8n Cloud** bills on **executions** — one whole workflow run, regardless of how many nodes it contains. A twenty-node run is one execution. Cost scales with how *often* you run, not how complex each run is.
- **n8n self-hosted** removes the meter entirely — free, unlimited executions, for the price of a server.

**A concrete example.** Take a scenario that processes a batch of 100 records each run — an iterator plus a few modules per item, say 4 operations per record. On Make that's ~400 operations *per run*; run it daily and you're at ~12,000 operations a month from one scenario, climbing tiers as you add more. On n8n Cloud, that same daily run is *one execution per day* — about 30 executions a month, regardless of the 100 records or the modules — trivially inside the entry plan. Self-hosted, it's free. That's the structural gap: Make meters the *work inside* each run; n8n meters the *runs*.

The practical consequence: the more elaborate your workflows, the more Make's per-operation model costs relative to n8n's per-execution model — and self-hosted n8n is dramatically cheaper at any real scale. Make's price buys a polished managed experience; n8n's buys ownership and near-free scale if you'll run it yourself. Compare the detail in our [n8n pricing guide](/articles/n8n-pricing).

## Ease of use and the visual experience — Make's edge

This is Make's clearest win. Its canvas is genuinely the most refined visual builder in the category: laying out a branching scenario, watching data flow module-to-module, and debugging visually is a pleasure, and non-developers who still need real branching get further on Make than on n8n. n8n's canvas is capable but more utilitarian and assumes more technical fluency. If you want power *and* polish without writing code, Make is the friendlier of the two power tools.

## Code and extensibility — n8n's edge

Make has code modules, but n8n treats code as first-class: JavaScript or Python nodes throughout, custom nodes you can build and share, and full self-hosting. When a scenario needs logic neither tool's modules express, n8n lets you simply write it; on Make you're more often working within the module set. For engineering teams, that difference is the reason to pick n8n — you can bend it to anything.

## AI — n8n goes deeper

Both are adding AI, and Make's AI modules are solid for dropping intelligence into a visual scenario. But n8n goes further: a real **AI-Agent framework** on LangChain, first-class **RAG** with vector stores (Pinecone, Qdrant, Supabase), multi-agent patterns, and **your own model and key** — so you control what runs and, self-hosted, keep data in-house. For building agentic, data-grounded AI, n8n is ahead; for a straightforward AI step inside a beautiful visual flow, Make is perfectly capable. Our [n8n AI playbook](/articles/n8n-ai-playbook) shows how deep the n8n side goes.

## Self-hosting and data ownership — n8n only

Make is hosted-only; your data flows through its cloud. n8n can run entirely on your own infrastructure, so regulated or sensitive data never leaves it — often the deciding factor for finance, healthcare and legal teams, and the reason n8n's cost is so low at scale. If self-hosting or strict data residency is a hard requirement, n8n is the only one of the two that can meet it.

## Catalog and maturity — Make leads on breadth

Make's 3,000+ app catalog is considerably larger than n8n's 400+, with more ready-made connectors for niche tools. n8n closes most of the gap with its HTTP node and code, but "Make already has a polished module" versus "n8n needs a small build" is a real, everyday difference. Both are mature, well-documented platforms with active communities — n8n's open-source community is enormous (175,000+ GitHub stars), while Make's is a large, hosted-SaaS user base.

## When each wins — by scenario

- **An elaborate, multi-branch scenario built by a non-developer who wants a beautiful visual canvas:** **Make**.
- **A workflow that needs custom code or logic the modules don't express:** **n8n**.
- **Anything touching sensitive or regulated data:** **n8n self-hosted** — data stays in-house.
- **High-volume or very elaborate workflows where cost matters:** **n8n** — per-execution and free self-hosting beat per-operation at scale.
- **A serious AI agent with retrieval over your own documents:** **n8n** — deeper agent/RAG tooling, your own model.
- **A niche app only Make supports natively, with zero build:** **Make** — catalog breadth is the tie-breaker.

## Which should you pick?

**Choose Make if:** you want the most polished visual builder, you have non-developers who still need real branching, you value a larger catalog with ready-made connectors, and you're happy on a hosted platform. **Choose n8n if:** you have technical capacity, you want to self-host for cost or data control, you need real code or the deepest AI, or your workflows are elaborate/high-volume enough that per-operation pricing hurts. Both are excellent power tools — the decision is ownership-and-code (n8n) versus polish-and-breadth (Make).

## By team profile — the honest pick

- **Non-technical team that wants power without code:** **Make.** Its polished visual canvas lets non-developers build serious branching logic, and the larger catalog means fewer build steps. n8n would demand more technical fluency than you have on hand.
- **Engineering or technical team:** **n8n.** You'll use the code nodes, want the AI depth, and likely prefer self-hosting for cost and control — Make's no-code-first model and hosted-only nature would constrain you.
- **Team with elaborate, high-volume scenarios:** **n8n.** Make's per-operation billing multiplies with complexity and volume; n8n's per-execution model (and free self-hosting) keeps elaborate workflows affordable.
- **Privacy- or compliance-sensitive business:** **n8n self-hosted.** Data stays on your infrastructure — Make, hosted-only, can't offer that, and it's often the deciding requirement regardless of polish.
- **Team building serious AI agents:** **n8n.** Its LangChain/RAG/agent tooling and your-own-model approach go well beyond Make's AI modules.
- **Team that values a beautiful, low-friction building experience above all:** **Make.** If the day-to-day joy of building and debugging visually matters most and you don't need code or self-hosting, Make is the nicer tool to live in.

The pattern: Make wins on *visual polish and catalog breadth* for teams happy on a hosted platform; n8n wins on *code, AI depth, data ownership and cost at scale* for technical teams. Both are genuine power tools — your team's profile, not a feature war, decides it. And if you're on the fence, weigh the trajectory: a team that will grow more technical, more AI-driven or more cost-sensitive over time leans toward n8n, whose ceiling and free self-hosting reward that direction; a team that will stay firmly no-code and values the visual building experience above all else is happier staying on Make. The honest tie-breaker is rarely a feature — it's whether you'll want to write code and own your infrastructure a year from now, or keep everything visual and fully managed for you.

## A note on trying before you commit

Neither tool imports the other's workflows, so switching means rebuilding by hand — choose deliberately. The low-risk way to decide: build your two or three most important scenarios on each. Make has a free tier to prototype on; n8n gives you a free self-hosted edition or a 14-day Cloud trial. Building the *same* real workflow on both for an afternoon tells you more than any feature table — you'll feel immediately whether Make's polished canvas or n8n's code-and-ownership fits how your team works. And because n8n workflows export as JSON, starting there keeps your logic portable if you ever need to move.

## The bottom line

n8n vs Make isn't simple vs powerful — it's two powerful tools optimized for different priorities. Make is the best hosted, visual, no-code power tool, with the widest catalog and the most refined canvas. n8n is the best control-and-AI power tool: self-hostable, code-extensible, with deeper AI and near-free scale for teams that run their own infrastructure. If ownership, code and AI matter most, n8n is the pick; if visual polish and catalog breadth matter most, Make is. For the full evaluation, see our [n8n review](/articles/n8n-review); to weigh cost, the [pricing guide](/articles/n8n-pricing) breaks down both meters.

## References

[1] n8n — official pricing — https://n8n.io/pricing/ (2026-07)
[2] n8n — features, AI & self-hosting — https://n8n.io/ (2026-07)
[3] Make — official pricing — https://www.make.com/en/pricing (2026-07)