n8n vs Zapier vs Make (2026): A Technical Founder's Honest Take

Every comparison article on this topic opens the same way: "Zapier is for beginners, Make is for the middle ground, n8n is for developers." Then they pad it with pricing tables and call it a day.

That's not wrong. It's just incomplete.

We've built production automation workflows on all three platforms — for e-commerce brands, a dealership management company juggling five different DMS systems, and a laundry services business that was drowning in manual operations. We've felt the pricing sting on Zapier when a client's workflows scaled, hit Make's polling trap at 2 AM, and self-hosted n8n on AWS for a total stack cost of ₹2,000 a month.

This is what we know from actually building — not from reading documentation.

The Short Answer (If You're in a Hurry)

Our default: n8n, self-hosted, every time we can. But read on — because there are legitimate reasons to pick the others.

Why Pricing Is the First Conversation, Not the Last

Most comparison articles bury pricing at the bottom. We put it here because for clients with growing automation needs, the pricing model determines whether automation is a competitive advantage or a runaway cost center.

Zapier charges per task. A task = one successful action step. A workflow with 10 steps that runs 1,000 times a month = 10,000 tasks. At that volume, you're looking at $99–$200/month on Zapier — before you've added any AI features, before your client's business grows, and before you've hit any of the more complex looping logic modern workflows actually require.

Here's where it gets worse: Zapier's model punishes complexity. An AI reasoning loop that drafts, critiques, and rewrites an email? That's three task units per run. A loop processing 500 rows from a sheet with 4 sub-steps? That's 2,000 tasks per loop execution. The more sophisticated your automation, the faster you hit the ceiling.

Make charges per operation — similar principle, but generally 50–60% cheaper than Zapier for equivalent volumes. The catch nobody mentions: Make's polling triggers consume operations even when no new data is found. A workflow that checks an inbox every 5 minutes burns operations on every check, not just when emails arrive. At scale, this is a meaningful hidden cost.

n8n charges per execution. One complete workflow run — whether it has 5 nodes or 500 — counts as one execution. That loop processing 500 rows with AI decisions at each step? Still one execution.

And if you self-host n8n, you pay nothing to n8n at all. Your only cost is infrastructure.

We deployed n8n on AWS EC2, paired it with NocoDB as the open-source data layer, S3 for storage, and connected it to the OpenAI API for AI processing. The total platform cost for a laundry services client running over 1,000 automated workflows a month came to ₹2,000/month — all-in. API costs were on actuals (pay-for-what-you-use), and because everything was open-source, there were no per-seat or per-execution fees. The client's workflow volume kept growing. The ₹2,000 didn't.

Run that same operation on Zapier's task-based model and you'd be looking at multiple times that figure — just in platform fees — before the workflows became truly complex.

The Learning Curve Is a Myth (With an Asterisk)

Every article says n8n has a steep learning curve. We'd push back on that.

For developers with solid fundamentals, n8n is not hard. If you understand APIs, JSON, basic JavaScript, and how data flows between services, you'll be productive in n8n within a day. The node-based architecture is intuitive for anyone who's built backend systems. You're essentially drawing a flowchart of your data pipeline — and in n8n 2.0, the interface is cleaner than ever.

The "steep learning curve" is real, but only for non-technical users. And that's the honest separation point: n8n requires you to understand what you're building. You need to write some JavaScript in the Code node for complex transformations. You need to understand data structures and how to design a workflow that doesn't create infinite loops or silent failures. For a marketing ops person who just wants to push a Typeform lead into HubSpot, that's too much to ask.

For a technical founder, an engineering team, or a dev agency like ours — it's genuinely not steep. It's just engineering.

Zapier's no-code experience is real and valuable. If you hand it to a non-technical team member and tell them to build a Zap, they probably can. That's not nothing. Make requires understanding conditional logic and data routing, which edges out most casual users. n8n assumes you're a builder.

AI Automation in 2026: Where n8n Pulls Away

The 2025–2026 period fundamentally changed what we expect from automation platforms. We're not just connecting apps anymore — we're orchestrating AI agents that reason, branch, and self-correct.

All three platforms now connect to OpenAI, Claude, and Gemini. But the depth of that integration is not equal.

Zapier Agents (launched 2026) let you create autonomous AI systems that act across your connected apps. It's impressive for no-code use cases — marketing teams can set up agents without engineering help. The limitation is the same as Zapier's overall philosophy: you're working within predefined boundaries.

Make AI Agents are functional and visually intuitive to configure. Good for straightforward AI-assisted workflows where you're calling an LLM and routing the output.

n8n's AI Agent Tool Node (n8n 2.0, December 2025) is where serious AI automation work happens. Native LangChain integration means you can build multi-agent pipelines — agents that call other agents, maintain persistent memory across runs, and use vector databases for retrieval-augmented generation (RAG). You can run your own self-hosted LLMs alongside n8n and keep sensitive data completely within your infrastructure. No data ever leaves your servers.

We built a document management automation system (DMS) for a client operating across multiple dealership platforms. The company had five different DMS softwares and was manually cross-referencing data between all of them daily. We built an n8n pipeline that automated the entire data flow and gave them a single source of truth — one system they actually trust, no more daily manual reconciliation across platforms. That kind of workflow — pulling from multiple proprietary APIs, transforming mismatched data schemas, running conditional logic and feeding into a central NocoDB database — is where n8n's architecture genuinely shines. Make could have handled parts of it. Zapier couldn't have handled it at a reasonable cost.

As an AI automation partner, we've found that clients who start with simple Zaps eventually hit the ceiling. The question is when — and whether they're locked into a pricing model that punishes growth by then.

Integration Depth: Where Zapier Still Leads

To be fair: Zapier's 8,000+ native integrations are a genuine advantage. Make has 3,000+. n8n ships with around 1,500 native nodes.

For most workflows, this doesn't matter. The apps that actually run businesses — Google Workspace, Slack, Notion, HubSpot, Shopify, Airtable, Stripe, Twilio, major CRMs — are well-supported on all three.

Where Zapier pulls ahead is niche SaaS tools. If your client uses some obscure HR platform or industry-specific software from 2009, Zapier probably has a pre-built connector. n8n might not.

But here's the thing: n8n's HTTP Request node lets you connect to any service with a REST API. You can paste a cURL command and n8n generates the connection setup. For a developer, building a custom integration with an API-accessible tool takes an hour. It's not the same as a pre-built connector, but it's not a blocker either.

For non-developers who need that obscure connector to just exist and work without custom code — Zapier is the answer. For technical teams, n8n's 1,500 native nodes plus HTTP Request covers essentially everything.

When to Use Each: Our Actual Recommendation

Choose Zapier when:

• Your client's team will build and maintain automations themselves (non-technical)
• The use case is genuinely simple — a few linear steps, low volume
• You need a connector for a niche SaaS tool that isn't on n8n or Make
• Time-to-live matters more than cost — you need something working today with no setup

Choose Make when:

• You need visual, complex conditional logic and your team is comfortable with flowchart thinking
• Volume is moderate and you want better pricing than Zapier without the infra overhead of self-hosting
• You're dealing with sophisticated data transformation and want a visual canvas to debug it
• You don't have a developer available to manage a server

Choose n8n when:

• Volume is high or growing — self-hosted n8n's economics become dramatic at scale
• You're building AI-native workflows: agents, LangChain pipelines, RAG systems
• Data privacy or sovereignty matters — healthcare, finance, clients with sensitive data
• Your team has developers who can manage a VPS (it's less work than it sounds)
• You're an agency or dev shop doing this for clients and want to own the stack

For our clients, the conversation usually starts with: "Do you have a developer who can manage a simple cloud server?" If yes, n8n self-hosted is almost always the right call. If no, we evaluate volume and complexity — Make for anything non-trivial, Zapier only for genuinely simple, low-volume workflows where the client will manage it themselves.

The Real Hidden Cost Nobody Talks About

When Zapier publishes pieces about n8n's "hidden infrastructure costs," they're not wrong — but they're also not being fully honest.

Yes, self-hosting n8n means you manage a server. For an enterprise with zero DevOps capability, that's a real burden. For a technical team or an agency managing client infrastructure, it's an afternoon of setup and a monthly check-in. The "hidden cost" argument assumes you have no engineering capacity at all.

The hidden cost in the other direction — the one that never makes it into Zapier's blog posts — is the migration tax. When you outgrow Zapier's pricing model, rebuilding 50+ workflows on another platform is painful. We've seen clients stay on expensive Zapier plans longer than makes sense because the migration effort feels too high. Starting on n8n avoids that entirely.

For clients who want to understand what AI-powered workflow automation can look like for their specific business, we offer a no-obligation automation discovery session. The stack recommendation comes after we understand the actual use case — not before.

Our Verdict

n8n wins for technical teams and agencies. The economics at scale are not close. The AI capabilities in 2026 are not close. The data control story is not available on the other two at all. For the work we do — building automation systems for businesses with real volume, real complexity, and growing AI requirements — n8n self-hosted is the default answer.

Make is a legitimate choice for mid-complexity workflows where you want visual power without managing infrastructure. Don't dismiss it.

Zapier still owns the non-technical user. If your client's marketing team is going to build and manage their own automations, Zapier's UX advantage is real and worth paying for.

The tool that wins is the tool that matches your team's capability and your client's growth trajectory. Start with that question — not the pricing page.

Frequently Asked Questions

Is n8n really free to self-host?
The n8n Community Edition software is free to download and run on your own server. You pay only for the infrastructure — a basic VPS costs $5–$20/month. For high-volume workflows, self-hosted n8n is dramatically cheaper than any cloud automation platform.

Can non-developers use n8n?
Honest answer: not well. n8n requires some JavaScript knowledge for complex data transformations and an understanding of API architecture. For simple workflows, the visual interface is manageable — but to use n8n properly, you need technical fundamentals. If your team has none, start with Make or Zapier.

What's the difference between a Zapier "task" and an n8n "execution"?
In Zapier, every action step in a workflow counts as one task. A 10-step workflow that runs 1,000 times = 10,000 tasks billed. In n8n, one complete workflow run = one execution, regardless of how many steps it contains. For complex workflows, this difference is enormous.

Is Make cheaper than Zapier?
Generally yes — Make is roughly 50–60% cheaper than Zapier at equivalent workflow volumes. However, Make charges per operation, and its polling triggers consume operations even when no new data is found. Factor this into your cost estimates for high-frequency scheduled workflows.

Can n8n build AI agents?
Yes, and better than its competitors. n8n 2.0 (December 2025) introduced the AI Agent Tool Node with native LangChain integration, persistent memory, and support for self-hosted LLMs. For multi-agent orchestration, RAG pipelines, and complex AI workflows, n8n is the most capable of the three platforms.

Which tool is best for Shopify automation?
All three can connect to Shopify. n8n via HTTP Request or the Shopify node handles order flows, inventory sync, and customer data pipelines well. For Shopify merchants with high order volumes who want to connect to a CRM, Klaviyo, or custom fulfillment APIs, n8n's pricing model makes it the most scalable choice. If you're building a full Shopify automation stack, we typically pair n8n with the Shopify webhooks API rather than polling-based triggers for real-time order processing.

How long does it take to set up self-hosted n8n?
For a developer familiar with Linux and cloud servers, setting up n8n on a VPS (AWS EC2, DigitalOcean, etc.) takes 1–3 hours including SSL configuration. Docker makes the deployment straightforward. n8n's documentation covers the standard setup well.

What's Make's polling trap?
Make's trigger modules that use polling — checking for new data at regular intervals — consume operations on every check, not just when new data is found. A workflow polling every 5 minutes runs 8,640 checks per month. If most checks return no data, you're burning your operation allowance on empty polls. For event-driven workflows using webhooks, this isn't an issue. For polling-based triggers on a busy schedule, it adds up.

Should a startup start with Zapier or jump straight to n8n?
If your founding team includes developers: start with n8n self-hosted. The setup cost is worth it to avoid a painful migration later. If your founding team is non-technical and you need automation working this week: Zapier or Make gets you moving. Plan to revisit the stack when costs start biting.

Can I migrate from Zapier to n8n?
Yes, but there's no automated migration tool — you rebuild workflows manually. The logic transfers; the interface doesn't. For complex, production-critical workflows, plan for a parallel run period. Most agencies (including us) treat this as a scoping exercise where we audit existing Zaps before recommending a migration approach.

Rishabh Sethia, Founder & CEO of Innovatrix Infotech. Former Senior Software Engineer and Head of Engineering. DPIIT Recognized Startup. We build AI automation systems, Shopify development solutions, and full-stack web applications for businesses across India, the Middle East, and Singapore.

Originally published at Innovatrix Infotech