n8n vs Make: An Honest Comparison From Someone Who Uses Both

If you are comparing n8n and Make (formerly Integromat), you are already looking at two of the best workflow automation platforms available right now. Both of them leave Zapier in the dust when it comes to power and flexibility, so whichever you choose, you are starting from a strong position.

I have been building automations professionally for startups across Latin America for the past few years. Make was my go-to tool when it was still called Integromat, and I switched to n8n about two years ago when I needed self-hosting and deeper code integration for client projects. Today I still use both — Make for a handful of client accounts that were already set up there, and n8n for everything new.

This comparison is based on that daily experience, not on spec sheets. I will walk you through pricing, visual builders, integrations, AI capabilities, self-hosting, code flexibility, and error handling, then give you a clear recommendation based on your situation.

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TL;DR — Quick Comparison Table

Category	n8n	Make (formerly Integromat)
Pricing model	Per workflow execution	Per operation (per node)
Free tier	Community Edition (self-hosted, unlimited)	1,000 operations/month
Starting price	20 EUR/month (Starter)	$10.59/month (Core)
Self-hosting	Yes (Docker, Kubernetes)	No
AI capabilities	Built-in AI agent builder	Basic AI modules
Code nodes	JavaScript and Python	Limited (basic scripting)
Native integrations	400+ (plus HTTP request node)	1,500+
Best for	Technical users, startups, self-hosters	Visual builders, non-developers, agencies

Bottom line: n8n wins on flexibility, pricing transparency, AI features, and self-hosting. Make wins on polish, native integrations count, and ease of onboarding for non-technical users.

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What Is n8n?

n8n is an open-source workflow automation platform that lets you connect apps, APIs, and services through a visual canvas. It was created by Jan Oberhauser in Berlin and has grown into one of the most popular automation tools in the developer and startup community.

What sets n8n apart is that it is genuinely open source. You can self-host it on your own server, inspect the code, and extend it however you want. There is also a cloud-hosted version if you prefer not to manage infrastructure.

I run my n8n instance on a small VPS and it handles around 40 active workflows for multiple client projects. The combination of a visual builder with JavaScript and Python code nodes makes it feel like a low-code tool that never hits a ceiling. If you want a deeper look at the platform, check out my full n8n review.

What Is Make (Formerly Integromat)?

Make, which rebranded from Integromat in 2022, is a cloud-only visual automation platform. It is known for having one of the most elegant visual builders in the industry. Scenarios (their term for workflows) are built by connecting circular modules on a canvas, and the drag-and-drop experience is genuinely enjoyable.

Make has been around since 2012 (as Integromat) and has a massive library of over 1,500 native integrations. It is particularly popular with marketing teams, agencies, and non-technical users who want powerful automation without writing a single line of code.

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Detailed Comparison: n8n vs Make

1. Pricing — The Biggest Difference

This is where the two tools diverge the most, and it is the number one reason I recommend people look closely before committing.

Make uses operation-based pricing. Every time data passes through a single node in your scenario, that counts as one operation. A five-step workflow that processes one record uses five operations. Process 100 records through that same workflow and you have used 500 operations.

Here are Make’s current plans:

• Free: 1,000 operations/month, 2 active scenarios
• Core: $10.59/month for 10,000 operations
• Pro: $18.82/month for 10,000 operations (adds priority execution, custom variables)
• Teams: $34.12/month for 10,000 operations (adds team features)

Additional operations can be purchased, but costs scale quickly at higher volumes.

n8n uses execution-based pricing. An execution is one complete run of a workflow, regardless of how many nodes it has. A workflow with 3 nodes and a workflow with 30 nodes both count as one execution.

Here are n8n’s cloud plans:

• Community (self-hosted): Free, unlimited executions
• Starter: 20 EUR/month for 2,500 executions
• Pro: 50 EUR/month for 10,000 executions
• Enterprise: Custom pricing

Real cost example: Let us say you have a workflow that triggers when a form is submitted, enriches the data via an API, creates a CRM record, sends a Slack notification, and logs it to a spreadsheet. That is 5 nodes.

If you process 1,000 form submissions per month:

• Make: 5 nodes x 1,000 runs = 5,000 operations. You need the Core plan at minimum, and you have used half your monthly budget on one scenario.
• n8n cloud: 1,000 executions. Well within the Starter plan.
• n8n self-hosted: Zero cost beyond your server (around $5-10/month for a VPS).

At 5,000 submissions per month, the gap widens dramatically. Make would consume 25,000 operations, forcing you to buy extra operation packs. n8n cloud would use 5,000 executions, still within the Pro plan.

This per-node operation counting is the single biggest drawback of Make’s pricing model. The more complex your workflows get, the faster you burn through operations. With n8n, complexity is essentially free.

If you want to explore n8n’s pricing and plans in detail, the Starter tier is generous enough for most solo users and small teams.

For a full breakdown of what each tier includes, see my n8n pricing guide.

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2. Visual Builder — Both Excellent, Different Strengths

Make and n8n both offer visual, canvas-based workflow builders. This is one area where both tools genuinely shine, and the choice comes down to personal taste.

Make’s builder uses circular module icons connected by lines. It is clean, colorful, and immediately intuitive. Scenarios flow left to right, and the visual feedback when data moves through the pipeline is one of the best I have seen. Make also handles branching and parallel execution paths elegantly. If you have ever used a flowchart tool, you will feel right at home.

n8n’s builder uses rectangular node cards on a freeform canvas. It is less visually polished than Make, but it is more flexible. You can arrange nodes however you want, create loops, add sticky notes for documentation, and the canvas supports complex branching patterns that would be awkward in Make’s more structured layout.

n8n also has an edge in debugging. You can pin test data to nodes, see the full input and output of every step, and execute individual nodes in isolation. Make has similar inspection tools, but n8n’s feel more developer-friendly.

My take: If I am showing automation to a non-technical client, I open Make. The visual polish makes an impression. If I am building something complex for production, I prefer n8n’s canvas because it handles messy, real-world workflows better.

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3. Integrations — Quantity vs. Flexibility

Make has over 1,500 native integrations and adds new ones regularly. If the app you need has a Make module, the setup is usually smooth, with pre-built fields, dropdown options, and helpful documentation. For popular tools like Google Workspace, Slack, HubSpot, Shopify, and Airtable, Make’s modules are excellent.

n8n has around 400+ native integrations, which is significantly fewer. However, n8n has a trump card: the HTTP Request node and the Code node. These two nodes together mean you can connect to literally any API that exists. I have built n8n integrations with Chilean banking APIs, obscure CRM systems, and custom internal tools that will never have a native module in any platform.

Make also has an HTTP module, but in my experience, n8n’s is more flexible, especially when you need to chain requests, handle pagination, or work with authentication schemes that are not OAuth2.

The practical difference: If you work primarily with mainstream SaaS tools and want plug-and-play setup, Make’s library is hard to beat. If you work with APIs, custom systems, or anything outside the mainstream, n8n gives you the tools to connect to anything.

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4. AI Capabilities — n8n Is Ahead

This is the area where n8n has pulled ahead most decisively in 2025 and 2026.

n8n has a dedicated AI agent builder that lets you create sophisticated AI workflows with tools like OpenAI, Anthropic Claude, Google Gemini, and open-source models. You can build autonomous agents that reason, use tools, access databases, and take actions. The AI nodes support:

• Chat-based agents with memory
• Retrieval-augmented generation (RAG) with vector stores
• Tool-calling agents that can trigger other n8n workflows
• Custom AI chains with structured outputs
• Support for local models via Ollama

I have built AI-powered customer support systems, document analysis pipelines, and content generation workflows in n8n that would be extremely difficult to replicate in Make.

Make has basic AI modules for OpenAI and a few other providers. You can send prompts and get completions, which covers simple use cases like summarizing text or generating drafts. But there is no agent framework, no RAG support, and no way to build the kind of multi-step AI reasoning workflows that n8n enables out of the box.

If AI-powered automation is part of your roadmap — and in 2026, it probably should be — n8n is the clear winner.

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5. Self-Hosting — n8n’s Killer Feature

n8n can be self-hosted. You can run it on your own server using Docker, deploy it on Kubernetes, or spin it up on a $5/month VPS from Hetzner or DigitalOcean. The entire codebase is open source under a sustainable-use license.

Make cannot be self-hosted. It is a cloud-only platform. Your data, your workflows, and your execution logs all live on Make’s servers.

Why does this matter?

• Data sovereignty: If you handle sensitive data for clients in regulated industries (healthcare, finance, government), self-hosting lets you keep everything on infrastructure you control. This is not optional in some jurisdictions — it is a legal requirement.
• Cost at scale: My self-hosted n8n instance runs on a VPS that costs me around 8 EUR/month and handles tens of thousands of executions. The equivalent n8n Cloud or Make plan would cost significantly more.
• No vendor lock-in: If n8n the company disappeared tomorrow, my workflows would keep running on my server. With Make, a shutdown or pricing change could leave you stranded.
• Customization: Self-hosting means you can add community nodes, modify configuration, and integrate with local services and databases on the same network.

For startups, agencies managing client data, and developers who want full control, self-hosting is a massive differentiator. It is the main reason I moved from Make to n8n, and I have not looked back.

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6. Code and Flexibility — n8n for Technical Users

n8n includes JavaScript and Python code nodes that let you write arbitrary code inside your workflows. Need to transform data in a way that no built-in node supports? Write a few lines of JavaScript. Need to call a Python library for data analysis? Use the Python node. You can also use npm packages in the Code node when self-hosting.

I regularly use Code nodes for:

• Complex data transformations that would take 10+ nodes to do visually
• Custom API authentication flows
• Mathematical calculations and data aggregation
• String manipulation with regex
• Interfacing with Supabase and PostgreSQL using custom queries

Make has limited coding capabilities. There is a basic scripting module and some text/math functions, but you cannot run arbitrary JavaScript or Python. For non-developers, this is actually fine — it keeps things simple. But for technical users, it is a hard ceiling.

n8n also supports:

• Custom nodes: You can build and share your own integration nodes.
• Expressions everywhere: Every field in n8n supports JavaScript expressions for dynamic values.
• External libraries: When self-hosting, you can install and use npm packages.

If you have a technical background — and if you are reading this comparison, you probably do — n8n gives you significantly more power.

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7. Error Handling — Different Approaches, Both Effective

Error handling is one of those things you do not think about until a critical workflow fails at 2 AM.

Make’s error handling is well-designed and visual. You can add error handler modules to any scenario, set up break/resume flows, configure retries, and create dedicated error routing paths. The visual representation of error flows is intuitive — you can see exactly where failures are caught and how they are handled. Make also has built-in incomplete execution storage, which saves failed executions so you can retry them later.

n8n’s error handling is more developer-oriented. You can set up error workflows that trigger when any workflow fails, configure retry logic per node, and use try/catch patterns with the Code node. n8n also lets you set up alerts via email or webhook when errors occur.

One area where n8n has an advantage is the Error Trigger node, which creates a dedicated workflow for handling errors from other workflows. This means you can build centralized error monitoring — one workflow that catches and logs errors from all your other workflows, sends Slack notifications, and stores error details in a database.

My take: Make’s error handling is more beginner-friendly. n8n’s is more powerful if you invest the time to set it up properly. Both are adequate for production use.

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Decision Matrix: Which Tool Should You Choose?

Choose n8n if…

• You want to self-host for data sovereignty or cost savings
• You have a technical background (comfortable with APIs, JavaScript, or Python)
• AI-powered automation is important to your use case
• You run high-volume workflows where per-operation pricing gets expensive
• You need to connect to custom APIs or internal systems
• You value open source and want to avoid vendor lock-in
• You are a startup or agency building automation for clients

Choose Make if…

• You prefer a polished, intuitive visual builder
• You work primarily with mainstream SaaS tools that have Make modules
• You are a non-technical user who wants powerful automation without code
• You need a specific integration from Make’s 1,500+ library
• You are an agency that builds automations for non-technical clients
• You want a mature cloud platform with no infrastructure to manage
• Your workflows are simple and low-volume (Make’s free tier is good for small use cases)

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My Verdict

After using both tools extensively, my recommendation is straightforward.

For most technical users, startups, and anyone with even basic developer skills, n8n is the better choice. The combination of self-hosting, fair execution-based pricing, JavaScript/Python code nodes, and the AI agent builder makes it the more capable and cost-effective platform. Every month, the gap in AI capabilities grows wider.

Make remains an excellent tool, and I would not try to convince someone to leave it if their workflows are running smoothly there. Its visual builder is best-in-class, its integration library is massive, and for non-technical users it is genuinely easier to learn.

But if you are starting fresh in 2026, especially if you are building anything that involves AI, custom APIs, or high-volume data processing, n8n gives you more room to grow.

I run all my production workflows on a self-hosted n8n instance, and the cost-to-capability ratio is unmatched. If you want to try it yourself, you can start with n8n Cloud and migrate to self-hosting later if you need it.

For a broader comparison that includes Zapier, check out my n8n vs Zapier comparison or the three-way comparison of n8n, Zapier, and Make.

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Frequently Asked Questions

Is n8n really free?

The self-hosted Community Edition is free and gives you unlimited workflows and executions. You need to provide your own server (a basic VPS costs around $5-10/month). The cloud-hosted version starts at 20 EUR/month. Either way, n8n is significantly cheaper than Make at scale because it counts executions per workflow, not per node.

Can I migrate my Make scenarios to n8n?

There is no one-click migration tool, but the process is manageable. Most Make scenarios can be recreated in n8n in a few hours. The logic translates directly — triggers, actions, filters, and routers all have n8n equivalents. If you have complex scenarios, I recommend migrating one at a time and running both platforms in parallel until you are confident everything works.

Which tool is better for beginners?

Make is easier to learn for complete beginners. The visual builder is more polished, the onboarding experience is smoother, and there is less to configure. n8n has a steeper initial learning curve, but it is not difficult — most people are comfortable within a few days. If you have any programming experience, you will probably find n8n more intuitive because it thinks the way developers think.

Does Make have a self-hosted option?

No. Make is exclusively a cloud-hosted platform. If you need to run automations on your own infrastructure for compliance, data sovereignty, or cost reasons, n8n is one of the few professional automation tools that supports self-hosting.

Which tool has better AI features in 2026?

n8n, by a significant margin. n8n has a complete AI agent framework with support for chat agents, RAG, tool calling, vector stores, and multiple LLM providers including local models. Make has basic AI modules that let you send prompts to OpenAI, but it lacks the agent infrastructure and advanced AI workflow capabilities that n8n offers. If AI automation is a priority, n8n is the clear choice right now.