n8n vs Zapier 2026: Why Zapier Fails for Serious Projects

When a client recently asked me to build an automation layer on top of their Payload CMS website, the first question was obvious: should we use Zapier or something else?

I had used Zapier for years. Quick setup, thousands of app integrations, and that satisfying feeling of connecting two services in five minutes. But as I started designing systems where the website is not just a marketing page but actual business infrastructure — where content, AI, and workflows need to reinforce each other — Zapier stopped being the right answer.

I moved my client work to self-hosted n8n, and after several months of running it in production alongside Payload CMS, I have a clear picture of when each tool makes sense, where Zapier falls short for serious builds, and why the choice matters more than most people realize.

This is not a feature checklist. It is a practical breakdown based on building real systems.

The real question is not which tool is better

Every "n8n vs Zapier" article frames this as a feature comparison. More integrations here, better UI there. That misses the point entirely.

The actual question is: what kind of system are you building?

If you are connecting a few SaaS tools together — new form submission goes to a spreadsheet, a Slack notification fires when someone signs up — Zapier is fine. It is genuinely good at that. The setup is fast, the app directory is massive, and you do not need to think about infrastructure.

But the moment your automation becomes part of how the business operates, not just how it notifies, you hit a different set of requirements. You need workflows that access internal APIs. You need data to stay on your servers. You need long-running processes that do not get killed after 30 seconds. You need to debug complex failures without squinting at a simplified error log.

That is where the tools diverge completely, and where Zapier's strengths become constraints.

Where Zapier starts breaking

I want to be specific here because the issues are not theoretical.

Cost scales with complexity, not just volume

Zapier charges per task. Every action step in a workflow counts. The free plan gives you 100 tasks per month — that vanishes within days on any real project. Professional starts at roughly $20/month for 750 tasks, and once you hit 2,000 tasks you are looking at over $100/month. Push to 5,000 tasks and costs jump past $300/month.

The real problem is not the price itself. It is how the pricing model changes how you build. When every step costs money, you start optimizing for the bill instead of for correctness. You skip validation steps. You combine actions that should be separate. You avoid branching logic because each path adds tasks. I have seen teams "design around the bill" — reducing workflow steps to keep costs down — which is exactly backwards. You should be designing for reliability and letting the tooling accommodate that.

Hard ceilings on what you can build

Zapier limits workflows to 100 steps. Code actions get 30 seconds of runtime and 256 MB of RAM. Instant triggers hit rate limits at 20,000 requests per five minutes. Polling triggers on free plans get throttled even further.

For simple integrations, none of this matters. For anything that processes documents, handles batches, runs multi-step AI enrichment, or coordinates across several systems, these ceilings become walls. You cannot build a document processing pipeline that extracts text, runs it through an LLM, enriches the result, and stores it back in your CMS — all within 30 seconds and 256 MB.

Debugging is designed for simplicity, not for production

Zapier's error logs are built for non-technical users. That is a feature when you are connecting Gmail to a spreadsheet. It is a problem when your multi-branch workflow fails at step 14 and you need to understand why.

There is no built-in version control for Zaps. If 95% of runs error within a seven-day window, the Zap auto-pauses and you have to manually re-enable it. The task counting rules are nuanced enough that correlating runtime behavior with billable usage requires careful study of their documentation. Internal tools like Filter, Paths, Delay, and Storage do not count as tasks, which means they can silently do work that is invisible in your usage stats.

For a solo founder running five simple automations, this is manageable. For a business running critical workflows, it creates blind spots.

Why n8n works for infrastructure-grade automation

n8n solves a different problem. It is open source, self-hosted, and designed for people who want full control over their automation layer. You run it on your own server, connect it to your own databases, and own every piece of data that flows through it.

Here is what that means in practice.

No per-task pricing

This is the most obvious difference and it compounds over time. Whether your workflow runs 100 times or 100,000 times, the cost is your server. A decent VPS running n8n alongside Payload CMS and a database costs a fraction of what Zapier charges at equivalent volume.

More importantly, it removes the incentive to cut corners. You add the validation step. You include the error handling branch. You build the workflow correctly because there is no per-step penalty for thoroughness.

Your data never leaves your network

When you self-host n8n, workflows execute on your infrastructure. API credentials stay on your server. Customer data never passes through a third-party SaaS. This is not just a compliance checkbox — it is a fundamental architectural decision about who controls your business data.

For any system where the CMS, the automation layer, and the AI components need to share data, having everything on the same network simplifies architecture dramatically. n8n can call your Payload CMS API on localhost. It can query your database directly. It can trigger webhooks internally without ever touching the public internet.

Complex workflows are first-class

n8n supports loops, sub-workflows, error handling branches, custom code nodes in JavaScript and Python, and long-running processes. There is no 100-step limit and no 30-second execution ceiling. If your workflow needs to process a batch of 500 documents, call an LLM for each one, and write the results back to your CMS, you build that workflow and it runs until it finishes.

You can also run n8n in queue mode with multiple workers for horizontal scaling, which means heavy workflows do not block lighter ones. This is the kind of capability you need when automation is part of the system, not just a notification layer.

The trade-offs you need to accept with n8n

I would be dishonest if I did not cover what self-hosting n8n actually requires. It is not plug-and-play, and pretending otherwise would waste your time.

You own the infrastructure

Self-hosting means you are responsible for upgrades, backups, monitoring, and security patching. n8n releases new versions almost weekly, and not every upgrade is smooth. I have seen database migrations fail between certain version jumps, leaving the instance in a crash loop until you roll back. The fix is always the same — maintain good backups and test upgrades on a staging instance first — but it requires discipline and some DevOps comfort.

Security is your responsibility

n8n ships with powerful nodes — SSH, Git, Execute Command, Python Code — that can do almost anything on your server. That power is also a risk surface. Between December 2025 and February 2026, several critical security advisories were published, including remote code execution vulnerabilities in the Merge node, Git node, and Python Code node.

The n8n team patches these promptly, but you need to apply those patches yourself. If you expose n8n to the internet without proper hardening, restrict workflow editing to trusted users, and keep it updated, the risk is manageable. If you ignore security hygiene, you are running a very capable tool with very real attack vectors.

Memory behavior needs attention

n8n can consume more RAM than you expect, especially at idle. I have seen instances using 1 to 1.5 GB just sitting there with a handful of scheduled workflows. Workflows that process files — particularly PDFs — can hit memory limits even when the host server has plenty of free RAM. The solution is usually to increase container memory limits, use queue mode to isolate workers, or offload heavy processing to external services.

None of this is a dealbreaker, but it means you should treat n8n as a proper production service, not a set-and-forget tool.

How n8n fits with Payload CMS as a system

This is the part most comparison articles never cover because they treat automation tools in isolation. In reality, the automation layer is only as useful as the system it connects to.

When I build Payload CMS websites that function as business infrastructure — serving customers, employees, and AI simultaneously — n8n becomes the orchestration layer that ties everything together.

Content changes in Payload trigger n8n workflows that update vector stores, refresh caches, and distribute content across channels. Lead interactions captured through the website flow through n8n for enrichment, scoring, and CRM synchronization. Documents uploaded through the CMS get processed, indexed, and made searchable through automated pipelines. SEO metadata gets generated and validated without manual intervention.

The key insight is that both Payload CMS and n8n are self-hosted, API-driven, and designed for developers. They speak the same language. Payload exposes a REST API and webhooks natively, n8n consumes those webhooks and calls those APIs with zero friction. There is no middleware, no third-party connector to maintain, and no external service that might change its API or pricing.

This is what I mean when I say the website becomes a control surface. The CMS holds structured content, the automation layer moves and transforms it, and AI components consume it — all on infrastructure you own.

When you should still use Zapier

I am not going to pretend n8n is always the right choice. Zapier genuinely wins in specific scenarios.

If you are a solo founder connecting mainstream SaaS tools and your workflow count stays under a dozen simple automations, Zapier's speed of setup and breadth of integrations (over 8,000 apps) is hard to beat. You do not need to provision a server, configure Docker, or think about database backups. You sign up, connect your apps, and it works.

If your organization has zero DevOps capacity and no interest in building it, self-hosted n8n introduces risk you are not equipped to manage. Zapier abstracts all of that away — uptime, security patching, scaling — and for teams that genuinely cannot or should not run their own infrastructure, that abstraction has real value.

If you need SOC 2 compliance and a vendor-managed SLA without doing the work yourself, Zapier Enterprise offers 99.9% uptime guarantees and SOC 2 Type II certification. Achieving equivalent compliance on self-hosted n8n requires you to build and audit that posture yourself.

The decision framework

After running both platforms across multiple projects, here is how I think about the choice.

Start with what you are actually building. If automation is a convenience layer — notifications, simple data passing between SaaS tools, low-volume triggers — Zapier is efficient and appropriate. Do not over-engineer it.

If automation is an operational component of your business system — if workflows need to process data, coordinate between internal tools, handle complex logic, or run alongside a CMS and AI layer — self-hosted n8n is the more honest choice. You will invest more time upfront in infrastructure, but you avoid the cost ceiling, the execution limits, and the architectural dependency on a platform you do not control.

The question I ask clients is simple: is your automation something you run, or something you depend on? If you depend on it, you should own it.

Conclusion

The n8n vs Zapier choice is not about features. It is about what your automation layer needs to be.

Zapier is a SaaS product that connects apps. It does that well, with enormous breadth and minimal setup. For lightweight automation, it is a good product at a fair price.

n8n is infrastructure. Self-hosted, open source, and designed to be part of systems where you need full control over data, execution, and architecture. It requires more investment to run properly, but it removes the constraints that matter most when automation is central to how your business operates.

For the kind of work I do — building Payload CMS websites that serve as operational business systems with AI and automation built in — n8n is the clear choice. It sits on the same server, speaks the same APIs, and scales without per-task penalties. The trade-offs are real, but they are the kind you manage through good engineering rather than the kind that limit what you can build.

If you are considering which automation platform to adopt and your use case goes beyond simple SaaS integrations, I hope this breakdown gives you a clearer picture of what each tool actually requires and where each one falls short.

Let me know in the comments if you have questions, and subscribe for more practical development guides.

Thanks, Matija