We build automation systems for a living, and we use all three of these platforms — so this isn't a listicle scraped from pricing pages. It's the comparison we walk clients through when they ask the most common question in this space: should we build on n8n, Zapier, or Make?
The short answer: Zapier for speed, Make for visual mid-complexity work, n8n for power, volume, and AI. The long answer — pricing traps, scaling costs, and where each one breaks — is below.
The 60-Second Verdict
| Zapier | Make | n8n | |
|---|---|---|---|
| Best for | Fast, simple connections between SaaS apps | Visual multi-step scenarios at moderate volume | Complex logic, high volume, AI agents, data control |
| Integrations | 7,000+ (largest library) | 2,000+ | 1,000+ native, plus generic HTTP for anything with an API |
| Pricing model | Per task (every step counts) | Per operation (every module counts) | Per execution (whole workflow = 1), or free self-hosted |
| Learning curve | Easiest | Moderate | Steepest, most capable |
| AI capabilities | AI steps, Zapier Agents | AI modules | Native AI agent nodes (LangChain), memory, tool-calling |
| Self-hosting | No | No | Yes (open source) |
Pricing: Where the Real Differences Hide
Sticker prices look similar. The models don't behave the same way as you scale:
- Zapier charges per task — every action step in a Zap consumes one. A 6-step workflow running 5,000 times a month is 25,000–30,000 tasks, which pushes you into plans costing hundreds of dollars monthly.
- Make charges per operation — same trap, cheaper rates. Mid-volume workflows usually cost 3–5× less than Zapier, which is why Make is the default "Zapier got expensive" migration.
- n8n charges per execution — a 40-node workflow that runs once costs one execution. At high volume this is dramatically cheaper, and self-hosting removes usage fees entirely (you pay for a small server and your own maintenance).
Rule of thumb: if your automations run under ~1,000 times a month with few steps, pricing barely matters — pick on ease. Past ~10,000 multi-step runs a month, n8n is usually an order of magnitude cheaper.
Capability: Where Each One Breaks
Zapier
Unbeatable integration coverage and the fastest setup — a marketer can connect a form to a CRM in five minutes. It strains when you need branching logic, loops, error recovery, or data transformation: multi-path Zaps exist but get expensive and hard to reason about. Zapier is glue, not an application platform.
Make
The visual scenario canvas is genuinely good — routers, iterators, and aggregators handle mid-complexity flows Zapier struggles with. The pain arrives in debugging: long scenarios with nested routers become spaghetti, and error handling at scale requires discipline the tool doesn't enforce.
n8n
Closest to a real development platform: branching, loops, code nodes (JavaScript/Python), sub-workflows, versioning, and proper error workflows with retries and alerting. Its AI agent tooling — LLM nodes with memory and tool-calling — is the strongest of the three, which matters now that most interesting automations have an AI step in them. The trade-off is that production-grade n8n benefits from someone technical; it's the tool we build most client systems on, but "capable" and "forgiving" aren't the same thing.
Which Should You Pick?
- Pick Zapier if you're non-technical, your flows are 2–3 steps, volume is low, and speed of setup matters more than cost.
- Pick Make if you've outgrown Zapier's pricing, think visually, and your flows are moderately complex but not mission-critical.
- Pick n8n if your workflows are high-volume or revenue-critical, involve AI agents, need custom logic, or handle data you'd rather keep on your own infrastructure.
- Go custom (code + APIs) when even n8n can't express it cleanly — heavy AI agents, real-time systems, or deep product integrations.
In practice, mature setups mix tools: Make or Zapier for lightweight internal glue, n8n or custom code for the systems that touch customers and revenue. That's how we architect client automation systems — the blueprint stage exists precisely to pick the right substrate per workflow rather than forcing everything onto one platform.
If you're mapping this decision for an e-commerce brand specifically, start with our complete guide to Shopify automation, or estimate what automation would save you with the ROI calculator.