n8n vs Make: Which Automation Platform Should You Choose?

n8n is the better automation platform for most technical teams. It costs less at scale, offers real self-hosting, and provides far more advanced AI capabilities. Make (formerly Integromat) has a more polished interface and a bigger native-integration library. But once you move past basic automations, n8n’s flexibility and cost savings become impossible to ignore.

Both platforms are serious Zapier alternatives (see our n8n vs Zapier comparison if that’s your actual choice) with visual workflow builders, hundreds of integrations, and active communities. The question isn’t whether they’re capable, they both are. The question is which one fits your specific needs.

Pick n8n if you want self-hosting, AI-powered workflows, cost savings at scale, or data sovereignty for GDPR compliance. Pick Make if you prefer a polished cloud interface, need obscure app integrations, or want the simplest possible learning curve. For power users and growing agencies, n8n delivers more value per dollar.

At a Glance: n8n vs Make Comparison

What Is n8n?

n8n (pronounced “n-eight-n”) is an open-source workflow automation platform built in Berlin. You connect apps using a visual canvas editor: drag nodes onto the workspace, draw connections between them, and your workflow runs.

What sets n8n apart is its fair-code license and self-hosting option. The Community Edition is genuinely free, unlimited workflows, unlimited executions, no artificial caps. You just need a server. With over 172,000 GitHub stars, n8n is one of the most popular open-source automation tools in existence.

n8n excels at complex workflows. You can branch, loop, merge, and call sub-workflows. You can write JavaScript or Python inside any node. You can build AI agents with LangChain integration. The platform rewards technical thinking: if you’re comfortable with APIs, JSON, and automation logic, n8n feels incredibly powerful.

The cloud version starts at $20 a month and handles hosting for you. But the real value is self-hosting: run n8n on a $5 a month VPS and get unlimited executions with complete data control.

What Is Make?

Make (Integromat before its 2022 rebrand) is a visual automation platform founded in the Czech Republic in 2012. It competes directly with Zapier and n8n, positioning itself as a more affordable alternative with powerful visual workflows.

Make’s strength is its polished, intuitive interface. Scenarios (Make’s term for workflows) appear as circular modules connected by lines, a different visual language from n8n’s canvas approach, and many users find it easier to parse at a glance.

With over 1,500 native integrations, Make connects to more apps out of the box than n8n. The platform handles branching, routing, iterating over arrays, and error handling, plus variables and basic data stores.

Make is cloud-only. There is no self-hosted version. All data flows through Make’s servers. They offer EU data center options for European businesses, but you never get the full data sovereignty that self-hosting provides. Pricing is based on operations, each action in a scenario counts as one, similar in spirit to Zapier’s task-based model.

Which Is Easier to Use?

Make is slightly easier for beginners. n8n is easier for complex work.

Make’s circular module design is visually distinctive and intuitive out of the box. Building a basic scenario takes 10 to 15 minutes for a first-timer. n8n’s canvas approach has more visual overhead initially: there are dozens of node types, the expression editor has its own syntax, and data flow isn’t obvious at first.

Here’s the key insight: the learning investment pays dividends. Once you understand n8n’s model, typically after a weekend of focused exploration, building complex workflows becomes faster and more natural. Branching, merging, and error handling stay visually clear even as logic gets complicated, where the same logic in Make’s circular layout tends to get cluttered.

If you’re building simple, linear automations and want to start immediately, Make is slightly easier. If you’re building anything with conditional logic, loops, or multiple branches, n8n’s canvas becomes a real advantage after the initial learning curve.

There’s a deeper question underneath the interface debate: how much control you want over the logic itself. Make keeps you inside guardrails, which is comforting early and limiting later. n8n lets you drop into raw JavaScript or Python whenever the visual layer gets in the way. If you want to understand that trade-off before you commit, our breakdown of visual versus code workflow tools covers where each approach pays off.

Which Has More Integrations?

Make wins on quantity. n8n wins on flexibility.

The numbers: Make offers 1,500 plus native integrations, n8n offers 400 plus, roughly a 4 to 1 gap on paper. In practice it’s much smaller than it looks. n8n’s HTTP Request node connects to any app with an API, and nearly every modern tool has one. Authentication setup takes 5 to 15 minutes instead of a pre-built connector click, but once configured it works just as well. n8n also supports community nodes, third-party integrations you can install with one click on a self-hosted instance.

For the most common business apps (Google Workspace, Slack, Microsoft 365, Notion, Airtable, HubSpot, Salesforce, Stripe, Shopify, GitHub, Postgres, MySQL, MongoDB) both platforms have native support. Where Make genuinely wins is niche and regional tools: that industry-specific app with 500 customers is more likely to have a native Make connector than an n8n one.

How Does Pricing Compare?

n8n wins decisively at any serious volume, but understanding why requires understanding how each platform counts usage.

Make counts credits (renamed from “operations” in August 2025, same mechanics): every module run in a scenario costs one credit, so a 5-module scenario run 100 times uses 500 credits, and AI-related steps consume more than one. n8n counts executions: one complete run of a workflow equals one execution regardless of how many nodes it contains, so a 20-node workflow and a 3-node workflow running once cost the same. This difference compounds hard at scale.

Make pricing

n8n pricing

Both n8n Cloud tiers also include a monthly allowance of AI credits for n8n’s built-in AI features (2,300 on Starter, 5,700 plus on Pro), which Make bills against the same credit pool as everything else.

Real-world scenarios

Freelancer, 5,000 operations a month, 5-step average workflow. Make costs about $9/month, n8n Cloud about $20/month, self-hosted n8n about $5 to $10 in hosting. At this volume Make is actually cheaper than n8n Cloud, but self-hosted n8n still beats both.

Small business, 50,000 operations a month. Make runs $99 to $199/month, n8n Cloud $50 to $100/month, self-hosted n8n $10 to $20 in hosting. The gap widens fast: Make now costs 2 to 4 times more than n8n Cloud, and 10 to 20 times more than self-hosted n8n.

Growing company, 500,000 operations a month. Make runs $500 to $1,500 plus a month, self-hosted n8n stays at $20 to $50 in hosting. At scale the difference is staggering, self-hosted n8n saves thousands of dollars a year. This is the math that drives technical teams and agencies to n8n.

Can You Self-Host?

n8n: yes, completely free. Make: no, never. This is a fundamental architectural difference that matters more than most people realize.

n8n’s Community Edition is open source (fair-code licensed). You can run it on your own infrastructure, a Linux VPS, a Docker container, a Kubernetes cluster. Your data never touches anyone else’s servers, your credentials stay on your hardware, your workflow logs live on your own drives. Self-hosting takes some technical ability, most teams get it running in an afternoon, and your only ongoing cost is the server itself.

Make is cloud-only, period. All workflows, data, and credentials flow through their infrastructure. EU data center options help with some compliance requirements, but you never get true data sovereignty.

Three groups care deeply about this: EU businesses needing GDPR compliance, regulated industries (healthcare, finance, government) that can’t send data to third-party clouds, and cost-conscious teams running high-volume automations where per-operation pricing would be prohibitive. There’s also a quieter fourth group: agencies. If you build automations for clients, self-hosted n8n with unlimited executions is how you protect margins, your cost is infrastructure, your revenue is client contracts. For a deeper look at that angle, see our n8n for enterprise comparison.

Which Has Better AI Capabilities?

n8n wins decisively here, it isn’t close. Both platforms added AI features over the past two years, but took very different approaches.

n8n went all in on AI infrastructure. The AI Agent node is a complete LangChain implementation inside a visual builder. You can build autonomous agents that reason and use tools, connect to OpenAI, Claude, Gemini, or local models via Ollama, add vector stores (Pinecone, Qdrant, Supabase, Weaviate) for RAG pipelines, build multi-turn conversations with persistent memory, and chain multiple models together with custom logic.

Make has AI features, but they’re more limited: connecting to OpenAI as an action step, using AI to transform or summarize data within a module. There’s no agent framework, no RAG pipeline support, no vector database integration.

If AI automation is a priority, and it should be, n8n provides enterprise-grade capability Make simply doesn’t match. For simple text processing either platform is fine. For agents, memory, and retrieval, n8n is in a different league.

Which Handles Errors Better?

n8n has more robust error handling. Make has decent basics.

n8n gives you several layers to work with:

• Dedicated error workflows that trigger automatically whenever any workflow fails, so you can route alerts to Slack, log the failure, or kick off a recovery process.
• Resume from failure point. Failed executions restart from the exact node that broke rather than the beginning, which matters when the first half of a workflow did real work (charged a card, created a record) you don’t want to repeat.
• Try or catch patterns built directly into the logic, plus per-node timeouts and configurable retries.

Make offers error handler modules, auto-replay of failed operations, and execution history. That is adequate for most standard scenarios, but it is less flexible when a failure carries real cost or when you need to recover mid-workflow instead of re-running from scratch. For simple flows the difference rarely bites. For business-critical automation where a silent failure means lost revenue or a broken customer experience, n8n’s granularity is worth the extra setup.

Which Builds More Complex Workflows?

n8n handles complexity better, though both platforms are fully capable for standard use cases.

n8n’s canvas is a genuine visual programming environment: unlimited parallel branches, merging results from multiple branches, looping over arrays with transformations, calling sub-workflows and passing data between them, switch nodes for multi-way routing, and custom JavaScript or Python anywhere. Make’s circular design handles most scenarios well but can get visually cluttered once logic gets genuinely complex, since the interface wasn’t built for that scale of workflow.

If your workloads lean heavily toward code-first, script-heavy pipelines, n8n is not the only self-hostable option worth weighing. Our n8n vs Windmill comparison looks at where a developer-centric platform pulls ahead of a visual-first one, and where n8n’s balance of visual and code still wins for mixed teams.

Data Privacy and GDPR Compliance

n8n provides true data sovereignty, self-hosted n8n means your data never leaves your infrastructure, credentials are encrypted on your own servers, and air-gapped deployment is possible. Make offers EU data center options, which covers many compliance scenarios, but can never offer what self-hosting provides: certainty that your data stays on hardware you control. For healthcare, finance, government, or any organization with strict data-handling requirements, that distinction is the whole decision.

Quick Decision Matrix: Which Platform for Your Situation?

Find your situation in the left column; the right column is the answer that the rest of this article justifies.

When Should You Pick Make?

Make is the right choice when you want a polished, fully managed experience with no server to think about, when you need a specific niche integration that only Make supports natively, when your team is non-technical and wants the gentlest possible learning curve, when you’re running under 10,000 operations a month where Make’s pricing is genuinely competitive, or when EU cloud hosting is sufficient for your compliance needs without the overhead of self-hosting.

When Should You Pick n8n?

n8n is the stronger choice when cost matters and you’re scaling past 10,000 operations a month, when you need self-hosting for GDPR, regulated-industry compliance, or air-gapped deployment, when you’re building AI-powered automation with agents or RAG, when your workflows involve real branching complexity, when you value open source and want to avoid vendor lock-in, or when you run an automation agency where unlimited self-hosted executions are what makes the margins work.

How Do You Migrate from Make to n8n?

There’s no automatic import tool, migration is manual recreation, but the process is straightforward:

• Audit every active Make scenario. Note the trigger, modules, conditional logic, and monthly operation count, then flag what’s critical versus nice-to-have.
• Set up n8n. Spin up n8n Cloud or a self-hosted Docker instance, about 30 minutes to stand up.
• Verify integration coverage for every app your scenarios touch, using the HTTP Request node for anything without a native connector.
• Recreate scenarios as workflows. Simple ones take 10 to 15 minutes, complex ones about an hour.
• Run both in parallel and compare outputs before cutting over, then cancel Make once everything has been stable on n8n for a week or two.

A typical small business with 15 to 25 active scenarios needs about 2 to 3 days of focused work. The workflow is nearly identical if you are coming from Zapier instead, and our step-by-step migrate from Zapier to n8n guide walks through the same audit-rebuild-verify pattern in more detail.

The Final Verdict

Choose n8n if you value cost savings at scale, need self-hosting for data sovereignty or compliance, want advanced AI capabilities, build complex multi-branch workflows, or run an agency where unlimited executions matter. n8n is the power user’s choice.

Choose Make if you want a polished cloud experience without server management, need specific native integrations n8n doesn’t have, prefer a slightly easier initial learning curve, or run low-volume automations where the pricing gap barely matters.

For most technical teams and growing agencies, n8n is the better long-term choice. The cost savings compound over time, the AI capabilities future-proof your automation stack, and the self-hosting option provides guarantees cloud-only platforms cannot match. Make is a genuinely good platform at what it does, but n8n’s combination of open source, self-hosting, advanced features, and compelling economics makes it the default for serious automation work.

If neither platform feels like an exact fit, it’s worth widening the field before you commit. Our roundup of the 7 best automation platform alternatives puts n8n and Make side by side with the other tools worth a look, so you can see exactly where each one lands.

Bottom line: Choose n8n if you care about cost at scale, self-hosting, data sovereignty, advanced AI, or complex branching logic, which covers most technical teams and agencies. Choose Make if you want the polished, zero-server cloud experience, need a niche native integration, or run low-volume automations where the pricing gap is negligible. When in doubt and you have any technical capacity, n8n is the safer long-term bet.

Ready to build your automation engine? If you need an expert to design and implement the workflows that will save you hundreds of hours a year, let’s talk.