n8n vs Zapier vs Make: Which Automation Platform for Your Business in 2026
A practical comparison of n8n, Zapier, and Make for mid-market companies in 2026. Cost, control, AI agent capabilities, and when each one wins.
If you're choosing a workflow automation platform in 2026, you have three serious contenders: n8n, Zapier, and Make. They all connect apps. They all run scheduled workflows. They all advertise AI agents. And they all charge differently — sometimes by an order of magnitude. This guide is the comparison we wish existed when we were picking between them for client projects.
We've shipped production workflows on all three. Some thoughts before the table: nobody is paying us to recommend any of these. We use n8n the most because it fits how we build, but Zapier and Make are the right choice in specific cases. Read the whole thing — the answer is rarely the same for two different problems.
The TL;DR table
| n8n | Zapier | Make (Integromat) | |
|---|---|---|---|
| Pricing model | Per-execution (cloud) or self-hosted (free) | Per-task / monthly tier | Per-operation |
| Self-hosting | Yes (free, open source) | No | No |
| Best for | Engineering-led teams, complex logic, AI agents | Non-technical users, high-volume simple workflows | Visual builders, branched logic, mid-complexity |
| Native AI agents | Yes (LangChain-style nodes) | Yes (limited) | Yes (limited) |
| Pre-built integrations (count) | ~500 | ~7,000 | ~1,800 |
| Code in workflows | JavaScript, Python (full) | Limited code blocks | Limited |
| Versioning / Git | Yes (in flow JSON) | No | No |
| Typical mid-market cost | €50–500/mo (cloud) or €0–80/mo (self-host VPS) | €500–5,000/mo | €100–1,500/mo |
When n8n wins
n8n is the most flexible of the three. It's open source, you can self-host it for the cost of a VPS, and the workflow definition is JSON you can put in Git. For engineering teams building serious automation — especially anything involving AI agents, custom logic, or compliance/data residency requirements — n8n almost always wins.
Where it shines:
- AI agent workflows: native LangChain-style nodes, easy to chain LLM calls with deterministic logic, built-in vector store integrations.
- Self-hosting on your own infrastructure when GDPR or industry compliance forbids sending data to third-party SaaS.
- Complex branching, error handling, and data transformation that would require dozens of Zapier zaps.
- Cost predictability for high-volume workflows. A self-hosted n8n VPS at €40/mo can run thousands of executions per day.
- Version control and code review workflows — your automations live in your Git repo alongside everything else.
Where it loses: integration breadth (~500 vs Zapier's 7,000) and a learning curve that punishes non-technical users. If your finance manager wants to glue together two SaaS tools without engineering help, n8n is overkill.
When Zapier wins
Zapier is the right answer when (a) the people building the workflows are not engineers, and (b) the workflows are mostly point-A-to-point-B with simple branching. The 7,000+ integration library is genuinely unmatched — if your stack includes a niche SaaS tool, it probably has a Zapier integration before n8n or Make.
Where it shines:
- Speed to first value: a non-technical user can ship a working zap in 15 minutes.
- Massive integration library — covers the long tail of B2B SaaS.
- Reliability: Zapier's infrastructure is mature, monitoring is solid, executions are reliable.
- Good for sales-ops, marketing-ops, and HR-ops teams who need automation without engineering bandwidth.
Where it loses: cost grows fast. We've audited mid-market teams paying €3,000–8,000/month for Zapier flows that would cost €200/month on n8n. Also: complex branching logic gets ugly fast (multi-step zaps with paths and filters become unmaintainable around 8–10 nodes).
When Make wins
Make sits in the middle. The visual builder is the best of the three for branched logic — you can see the full data flow at once, route based on conditions, and handle iteration over arrays naturally. It's cheaper than Zapier per operation, with more visual sophistication than n8n.
Where it shines:
- Visual debugging of complex flows — Make's scenario view is genuinely the clearest of the three.
- Mid-complexity workflows with branching: better than Zapier, easier than n8n.
- Per-operation pricing means you only pay for what you actually run.
- Good for ops/marketing teams that have outgrown Zapier's branching limits but don't have engineering resources for n8n.
Where it loses: no self-hosting (so GDPR concerns hit just like Zapier), AI agent capabilities are still maturing compared to n8n, and once you cross into very complex logic, you'll wish you had a real programming language.
The decision framework
Forget feature checklists. Pick based on these three questions:
1. Who's building the automations?
- Non-technical users → Zapier
- Mixed (ops + light technical) → Make
- Engineering-led → n8n
2. What's the worst-case workflow complexity?
- Mostly linear with simple filters → any of the three; pick on price
- Branched with iteration over arrays → Make or n8n
- Multi-step with custom code, AI agents, or external services → n8n
3. Do you have GDPR / data residency / on-prem requirements?
- Yes → n8n self-hosted (only one of the three that supports it)
- No → all three are options
The hidden cost: maintenance
All three platforms suffer from a common failure mode: the team that built the workflows leaves, and nobody else can debug them. This isn't unique to automation tools — it's a property of any system without code review, version control, or documentation.
If you're going to invest meaningfully in workflow automation, treat the workflows like code. Document the intent of each one. Use naming conventions. Test critical paths before deployment. Have at least two people who can debug a broken workflow at 11pm. n8n makes this dramatically easier (Git-friendly), but the discipline matters on every platform.
Our default recommendation in 2026
For mid-market companies (50–500 employees) building serious AI-driven automation: n8n self-hosted on a small VPS, with engineering ownership. Cost: ~€50/month plus the ongoing engineering time. Capability ceiling: very high.
For mid-market companies with strong ops/marketing teams but limited engineering: Make. Better mid-complexity story than Zapier, much cheaper at scale.
For small teams or specific use cases inside a larger company (e.g. a sales team that just needs CRM-to-Slack notifications): Zapier. Don't let perfect be the enemy of done.
If you're not sure where you fit, this is one of the things we cover in a discovery workshop. We'll look at your actual use cases, the team that will own the automations, and your data residency constraints, then give you a written recommendation. Often it's not a single platform — it's a mix.