n8n vs Make (2026): Which Automation Platform Should You Choose?

Primary keyword: n8n vs make

Disclosure: This page contains affiliate links. We may earn a commission if you sign up through our links, at no extra cost to you.

n8n vs Make: Which Automation Platform Wins in 2026?

You’re trying to automate your workflows and you’ve narrowed it down to n8n or Make (formerly Integromat). Both are excellent — and both are better than Zapier for most use cases. But they serve different users.

The short version: n8n is for builders who want power, flexibility, and self-hosting. Make is for visual thinkers who want to build fast without touching code.

Here’s the full breakdown.

Quick Comparison

Pricing: How They Actually Charge You

This is where n8n and Make diverge sharply — and where most comparison articles get it wrong.

n8n Pricing

n8n charges by workflow executions, not individual operations. That means a workflow with 15 steps counts as one execution, whether it touches 3 apps or 30.

• Community Edition: Free forever, self-hosted, unlimited everything
• Starter (cloud): Based on monthly executions
• Pro: For production workflows with team features
• Business: For companies under 100 employees
• Enterprise: Custom pricing

The killer advantage: self-hosting is free with no limits. If you have a $5/month VPS, you can run unlimited workflows at zero marginal cost.

Make Pricing

Make charges by operations — each action in your scenario counts. A 10-step workflow that runs 100 times = 1,000 operations.

• Free: 1,000 operations/month
• Core: $10.59/month for 10,000 ops
• Pro: Higher limits + priority execution
• Teams/Enterprise: Collaboration + advanced features

Make’s pricing is predictable but can scale fast. A busy workflow with 20 operations running 50 times/day = 30,000 ops/month — that’s already past the basic plan.

Verdict on Pricing

n8n wins on cost for high-volume automation. Self-hosting makes it essentially free. Make is more accessible for beginners but gets expensive at scale.

Ease of Use

Make: Built for Visual Thinkers

Make’s visual builder is genuinely beautiful. You drag modules onto a canvas, connect them with lines, and configure each step in clean modal windows. Data mapping uses a point-and-click system that non-technical users can learn in an afternoon.

The scenario builder shows data flowing through your automation in real-time when you test, which makes debugging intuitive. You can literally watch your data transform step by step.

Learning curve: ~2-4 hours to build your first useful automation.

n8n: Built for Builders

n8n’s interface is also visual, but it assumes more technical comfort. The node-based canvas looks similar to Make, but the configuration panels expose more options, more fields, and more power.

Where n8n shines is code integration. You can drop a JavaScript or Python node anywhere in your workflow and manipulate data however you want. For developers, this means no artificial limits — if you can code it, you can automate it.

Learning curve: ~4-8 hours for non-developers, ~1-2 hours for developers.

Verdict on Ease of Use

Make wins for non-technical users. The visual builder is more polished and the learning curve is gentler. If you’re a developer, n8n will feel more natural.

Integrations

Make has the edge in raw numbers: 1,800+ app integrations vs n8n’s 400+. But numbers don’t tell the whole story.

n8n compensates with:

• HTTP Request node: Connect to any API with a REST endpoint
• Custom nodes: Build your own integrations in JavaScript
• Community nodes: 600+ community-built integrations

In practice, if an app has an API (and in 2026, almost everything does), n8n can connect to it. Make’s advantage is that those connections come pre-built with friendly configuration screens.

Make wins for plug-and-play. n8n wins if you don’t mind building custom connections.

AI and Automation Intelligence

Both platforms have invested heavily in AI features for 2026.

n8n AI Capabilities

• LangChain integration: Build full AI agent workflows with tools, memory, and chains
• AI Agent node: Create autonomous agents that can use your other n8n nodes as tools
• Vector store support: Connect to Pinecone, Qdrant, Supabase for RAG workflows
• Code-based flexibility: Use any AI API with custom HTTP or code nodes

Make AI Capabilities

• OpenAI modules: GPT-4, DALL-E, Whisper integration
• AI-powered data transformation: Smart field mapping suggestions
• Scenario templates: Pre-built AI automation templates
• Module marketplace: Growing library of AI-specific modules

Verdict on AI

n8n wins decisively for AI workflows. The LangChain integration and AI Agent node let you build sophisticated AI pipelines that Make simply can’t match. If AI automation is your primary use case, n8n is the clear choice.

Self-Hosting and Data Privacy

This is n8n’s trump card. You can run n8n on:

• Your own server (Docker, npm, or binary)
• A $5/month VPS
• Your company’s Kubernetes cluster
• A Raspberry Pi in your closet

Your data never leaves your infrastructure. For companies with strict data sovereignty requirements, this is often the deciding factor.

Make is cloud-only. Your data flows through Make’s servers in the EU/US. They have solid security practices, but you can’t self-host.

n8n wins completely on self-hosting and data control.

Error Handling and Reliability

Both platforms handle errors well, but differently:

n8n offers retry logic, fallback paths, and the ability to write custom error handling in code. You can build sophisticated retry strategies with exponential backoff.

Make has error routes — you can define what happens when a module fails, including retry, ignore, rollback, or break. The visual error handling is intuitive.

Tie. Both handle errors well. n8n gives more granular control; Make makes it more visual.

Who Should Choose What?

Choose n8n if:

• You’re a developer or have developers on your team
• You want to self-host for cost savings or data privacy
• AI agent workflows are important to you
• You need high-volume automation without per-operation costs
• You want full code flexibility within your automations

Choose Make if:

• You’re non-technical or prefer visual building
• You want the widest selection of pre-built integrations
• You need to build automations quickly without learning code
• You’re an agency building automations for clients
• You want polished documentation and templates

Our Recommendation

For most readers of TheToolChief — solopreneurs and small teams building productivity stacks — we recommend starting with Make for its gentler learning curve, then considering n8n when you hit scaling costs or need more technical power.

If you’re already technical, go straight to n8n. The self-hosted Community Edition is one of the best free tools in the automation space.

→ Try n8n free (self-hosted or cloud) → Try Make free (1,000 ops/month)

Related comparisons:

• Zapier vs Make: Is Zapier worth the premium?
• Best no-code automation tools in 2026

Frequently Asked Questions

Can I use n8n and Make together?

Yes — many teams use both. Use Make for quick visual automations with pre-built integrations, and n8n for complex workflows, AI agents, or when you need to self-host.

Is n8n really free?

The Community Edition is free and unlimited if you self-host. The cloud version has paid plans starting based on execution volume. Self-hosting on a $5/month VPS is effectively free with no limits.

Which is better for AI automation in 2026?

n8n is the clear winner for AI. Its LangChain integration, AI Agent node, and vector store support let you build sophisticated AI agent workflows that Make can’t match.

Can Make handle complex enterprise workflows?

Yes, Make can handle enterprise workflows, but it shines with mid-complexity automations. For highly complex or custom workflows, n8n’s code flexibility wins.

What’s the main reason to choose Make over n8n?

Ease of use. Make’s visual builder is more polished, the learning curve is gentler, and the 1,800+ pre-built integrations mean you can connect apps without writing any code.

Can I migrate from Make to n8n?

Not automatically — you’ll need to rebuild workflows. The concepts transfer, but the node configurations differ. Consider this before switching platforms.