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

n8n is the better automation platform for most technical teams in 2026. It costs less at scale, offers self-hosting, and provides far more advanced AI capabilities. Make (formerly Integromat) has a more polished interface and more native integrations. But once you move past basic automations, n8n's flexibility and cost savings become impossible to ignore.

Both platforms are serious Zapier alternatives 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.

At a Glance: n8n vs Make Comparison🏆 n8n wins

What Is n8n?

n8n (pronounced "n-eight-n") is an open-source workflow automation platform built in Berlin, Germany. 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 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 (n8n Cloud) starts at $20/month and handles hosting for you. But the real magic is self-hosting: run n8n on a $5/month VPS and get unlimited executions with complete data control.

What Is Make?

Make (formerly Integromat before the 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. The visual builder is clean and well-designed. Scenarios (Make's term for workflows) appear as circular modules connected by lines. It looks different from n8n's canvas approach, and many users find it easier to understand at first glance.

With 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. It also offers variables, data stores (basic databases), and scheduling options.

Make is cloud-only. There's 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 operation. A scenario with 5 modules running once uses 5 operations. This is similar to Zapier's task-based pricing, though generally more affordable.

Which Is Easier to Use?🤝 Tie

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

Make's circular module design is visually distinctive and intuitive. New users often find it easier to understand the flow of data. The interface is polished, modern, and guides you through setup with helpful prompts. Building a basic scenario takes 10-15 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 flows in ways that aren't obvious at first. But 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. The canvas lets you see your entire automation at once. Branching, merging, and error handling are visually clear. Multi-step logic that would be confusing in Make's circular layout becomes transparent in n8n.

Both platforms have comprehensive documentation and active communities. Make has excellent video tutorials. n8n has learning paths and a more developer-oriented documentation style.

The lesson: 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 significant advantage after the initial learning curve.

Which Has More Integrations?

Make wins on quantity. n8n wins on flexibility.

The numbers: Make offers 1,500+ native integrations. n8n offers 400+. That's roughly a 4-to-1 gap on paper.

In practice, it's much smaller than it appears.

n8n's HTTP Request node connects to any app with an API — and nearly every modern tool has an API. Authentication setup takes 5-15 minutes instead of clicking a pre-built connector. But once configured, it works just as well. Technical users often prefer this approach because it gives them full control over exactly what data gets sent and received.

n8n also supports community nodes — third-party integrations built by other users. Self-host n8n and you can install community nodes with one click, extending the library well beyond the official 400.

The practical question: do both platforms cover the tools you actually use? For the most common business apps — Google Workspace, Slack, Microsoft 365, Notion, Airtable, HubSpot, Salesforce, Stripe, Shopify, GitHub, PostgreSQL, MySQL, MongoDB — the answer is yes. Both have native support.

Where Make genuinely wins: niche tools and regional apps. That industry-specific SaaS product with 500 customers? Make might have a native connector. n8n probably won't. You'd use the HTTP node.

The lesson: Check your critical apps against both platforms' integration lists. If Make has native connectors for tools n8n doesn't, and you don't want to deal with API configuration, that matters. If your stack uses mainstream tools, the integration gap is largely irrelevant.

How Does Pricing Compare?🏆 n8n wins

n8n wins decisively on price at any serious volume.

Understanding the pricing requires understanding how each platform counts usage.

How Make Counts Operations

Every action in a Make scenario counts as one operation. A scenario with 5 modules running once uses 5 operations. Run that same scenario 100 times, and you've used 500 operations.

This is similar to Zapier's task-based model, though Make is generally cheaper per operation.

How n8n Counts Executions

n8n counts workflow executions. One complete run of a workflow equals one execution — regardless of how many nodes it contains. A 20-node workflow running once? One execution. A 3-node workflow running once? Also one execution.

This fundamental difference becomes massive at scale. Multi-step workflows in n8n cost the same as simple ones. In Make, they cost proportionally more.

Make Pricing in 2026

Additional operations can be purchased. At higher volumes (100K+ operations), expect to pay $99-299+/month depending on your tier and add-on purchases.

n8n Pricing in 2026

Real-World Pricing Scenarios

Scenario 1: Freelancer (5,000 operations/month, 5-step average workflow)

At low volumes, Make is actually cheaper than n8n Cloud. But self-hosted n8n beats both.

Scenario 2: Small Business (50,000 operations/month)

The gap widens. Make costs 2-4x more than n8n Cloud, and 10-20x more than self-hosted n8n.

Scenario 3: Growing Company (500,000 operations/month)

At scale, the difference is staggering. Self-hosted n8n saves thousands of dollars annually. This is the math that drives technical teams to n8n.

The lesson: For light usage, Make is competitive or even cheaper than n8n Cloud. Past 10,000 operations per month, n8n's pricing model becomes dramatically more affordable. At high volumes, self-hosted n8n is essentially free compared to Make's per-operation costs.

Can You Self-Host?🏆 n8n wins

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, Docker container, Kubernetes cluster, or even a Raspberry Pi. Your data never touches anyone else's servers. Your credentials stay on your hardware. Your workflow logs live on your drives.

Self-hosting n8n requires some technical ability. You need to set up a server, configure Docker or a direct installation, set up a reverse proxy for HTTPS, and handle updates. It's not difficult — many teams get it running in an afternoon — but it's not zero-effort either.

The reward? Unlimited executions for free. Your only cost is the server itself. A $5-10/month VPS from Hetzner, DigitalOcean, or Vultr handles most workloads easily.

Make is cloud-only. Period. All workflows, all data, all credentials flow through their infrastructure. They offer EU data center options, which helps with some compliance requirements. But you never get true data sovereignty.

Three groups care deeply about self-hosting:

• EU businesses requiring GDPR compliance and data sovereignty
• Regulated industries (healthcare, finance, government) that cannot send data to third-party clouds
• Cost-conscious teams running high-volume automations where per-operation pricing would be prohibitive

There's also a less-discussed group: agencies. If you build automations for clients, self-hosted n8n with unlimited executions is how you make healthy margins. Your cost is infrastructure. Your revenue is client contracts. The economics work beautifully.

The lesson: If self-hosting matters for your situation — cost, privacy, compliance, or business model — n8n is your only option. Make simply cannot meet that requirement.

Which Has Better AI Capabilities?🏆 n8n wins

n8n wins decisively. This isn't even close.

Both platforms added AI features over the past two years. They 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, use tools, and make decisions
• Connect to OpenAI, Anthropic Claude, Google Gemini, or local models via Ollama
• Add vector stores (Pinecone, Qdrant, Supabase, Weaviate) for RAG pipelines
• Build multi-turn conversations with persistent memory
• Chain multiple models together with custom logic
• Write custom AI logic in Python or JavaScript

Real example: I built a customer support agent in n8n that reads incoming emails, searches a knowledge base using vector similarity, drafts contextual replies, and routes complex issues to human agents. One workflow. Built in an afternoon.

Make has AI features, but they're more limited. You can connect to OpenAI and other providers as action steps. You can use AI to transform or summarize data within modules. Basic AI operations are straightforward.

But Make doesn't have agent frameworks, RAG pipeline support, vector database integrations, or the kind of sophisticated AI orchestration that n8n offers. The gap is significant if you're building anything beyond simple "summarize this text" operations.

The lesson: If AI automation is a priority — and it should be in 2026 — n8n provides enterprise-grade AI capabilities that Make simply doesn't match. For basic AI operations, both work fine. For AI-powered systems with agents, memory, and retrieval, n8n is in a different league.

Which Handles Errors Better?🏆 n8n wins

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

Errors aren't theoretical in automation. A failed payment sync costs revenue. A broken lead-routing workflow loses sales. When something breaks at 3 AM, you need to know — and you need recovery options.

n8n's error handling is comprehensive:

• Error workflows: Define a separate workflow that triggers whenever any workflow fails. Send Slack alerts, log to a database, trigger recovery actions.
• Retry from failure point: Failed executions can resume from exactly where they stopped — not from the beginning.
• Try/catch patterns: Build error handling logic directly into workflows.
• Per-node timeouts: Set different timeout values for different nodes.
• Full execution data: Inspect every input and output at each step for debugging.

Make has error handling too:

• Error handlers: Add error handling modules to scenarios
• Auto-replay: Automatically retry failed operations
• Execution history: View past executions and their status
• Break and resume: Some ability to handle errors gracefully

Make's error handling is adequate for most scenarios. But n8n's approach — particularly error workflows and retry-from-failure — gives you more control when things go wrong in complex, mission-critical automations.

The lesson: For simple automations, both platforms handle errors reasonably. For business-critical workflows where failures have real costs, n8n's more sophisticated error management provides better protection.

Which Builds More Complex Workflows?🏆 n8n wins

n8n handles complexity better. Both are capable for standard use cases.

Both platforms support branching, looping, and conditional logic. Both can handle multi-step workflows with error handling. The differences emerge in how they approach very complex automations.

n8n's canvas is a true visual programming environment. You can:

• Branch into unlimited parallel paths
• Merge results from multiple branches
• Loop over arrays with complex transformations
• Call sub-workflows and pass data between them
• Use switch nodes for multi-way routing
• Wait for external events mid-workflow
• Write custom JavaScript or Python for any operation

Make's circular module design handles most scenarios but can become visually cluttered with highly complex logic. It supports routers, iterators, and aggregators. But the interface wasn't designed for the same level of workflow complexity that n8n targets.

Real example: A workflow that receives webhooks, enriches data from three APIs in parallel, merges results, applies business rules based on combined data, and routes to different outputs based on scores. In n8n, that's one clean workflow on one canvas. In Make, it's possible but harder to visualize and maintain.

The lesson: For 80% of automations — simple triggers, actions, and basic conditions — both platforms work well. For the remaining 20% where complexity matters, n8n's architecture scales better.

Data Privacy & GDPR Compliance🏆 n8n wins

n8n provides true data sovereignty. Make relies on cloud trust.

For European businesses, data privacy isn't optional. GDPR requires knowing where your data is processed and maintaining appropriate controls. For regulated industries, the requirements are even stricter.

n8n's self-hosted option delivers complete data sovereignty:

• Your data never leaves your infrastructure
• Credentials are encrypted and stored on your servers
• Workflow logs stay in your control
• You implement your own security policies
• Air-gapped deployment is possible

n8n is built by a Berlin-based company that deeply understands EU data requirements. The entire architecture supports compliance-first deployment.

Make offers EU data center options, which helps with some compliance scenarios. They're cloud-only, but you can ensure your data is processed in the EU. For many businesses, this is sufficient.

However, Make can never offer what self-hosted n8n provides: complete certainty that your data stays on hardware you control. For healthcare, finance, government, or any organization with strict data handling requirements, this distinction matters.

The lesson: If your compliance requirements can be met with EU cloud hosting, Make works. If you need true data sovereignty — data that never touches third-party infrastructure — self-hosted n8n is the only answer.

When Should You Pick Make?

Despite n8n's strengths, Make is the right choice in specific situations:

1. You want a polished, managed experience. Make's interface is clean and well-designed. If you prefer everything handled in the cloud without server management, Make delivers that seamlessly.
2. You need niche integrations. With 1,500+ native connectors, Make supports more obscure apps out of the box. If your workflow depends on specific tools that n8n doesn't natively support, Make might save you API configuration time.
3. Your team is non-technical. Make's learning curve is slightly gentler for people who've never built automations before. The circular visual design is intuitive for many users.
4. You're running low-volume automations. Under 10,000 operations per month, Make's pricing is competitive with n8n Cloud. If you don't need self-hosting, Make is a solid choice at this scale.
5. You need quick vendor support. Make offers responsive support for paid tiers. Some businesses value having someone to call when things break.
6. EU cloud hosting is sufficient for compliance. If your regulatory requirements allow cloud hosting with EU data residency, Make's EU data centers check that box without the complexity of self-hosting.

When Should You Pick n8n?

n8n is the stronger choice in most technical scenarios:

1. Cost matters and you're scaling. Past 10,000 operations per month, n8n's pricing model saves substantial money. Self-hosted n8n at high volumes costs 90%+ less than Make.
2. You need self-hosting. GDPR compliance, regulated industries, data sovereignty, air-gapped environments — if any of these apply, n8n is your only option.
3. You're building AI-powered automation. n8n's AI Agent node, LangChain integration, and vector store support make it the clear choice for sophisticated AI workflows.
4. Your workflows are complex. Multi-branch logic, sub-workflows, parallel processing, advanced error handling — n8n's canvas handles complexity more elegantly.
5. You value open source. Inspect the code, build custom nodes, contribute to the community, ensure vendor lock-in never becomes an issue.
6. You run an automation agency. Self-hosted n8n with unlimited executions is how profitable agencies work. Your cost is servers. Your revenue is client contracts.
7. You're comfortable with technology. APIs, JSON, Docker, expressions — if these aren't scary, n8n's power becomes fully accessible.
8. You're based in Europe and need compliance certainty. Self-hosted n8n with EU hosting is the gold standard for European data handling requirements.

How Do You Switch from Make to n8n?

Migrating from Make to n8n requires manual recreation — there's no automatic import tool. But the process is straightforward:

Step 1: Audit your Make scenarios

Document every active scenario. Note the trigger, the modules used, the conditional logic, and the monthly operation count. Identify which scenarios are critical versus nice-to-have.

Step 2: Set up n8n

Either sign up for n8n Cloud or self-host. For self-hosting, the Docker installation takes about 30 minutes following n8n's documentation.

Step 3: Verify integration coverage

Check that n8n supports every app your scenarios use. For native integrations, you'll have a direct equivalent. For apps without native n8n support, plan to use the HTTP Request node.

Step 4: Recreate scenarios as workflows

Most Make scenarios translate directly to n8n workflows. The visual builders are different but the logic is similar. Simple scenarios take 10-15 minutes. Complex ones might take an hour.

Step 5: Test in parallel

Keep your Make scenarios running while testing the n8n equivalents. Compare outputs. When the n8n workflow matches, deactivate the Make scenario.

Step 6: Cancel Make

After all workflows run stable on n8n for a week or two, cancel your Make subscription.

Timeline: A typical small business with 15-25 Make scenarios needs 2-3 days of focused work to migrate completely.

Frequently Asked Questions

The Final Verdict

The choice depends on your priorities:

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 pricing differences are minimal.

For most technical teams and growing businesses, n8n is the better long-term choice. The cost savings compound over time. The AI capabilities future-proof your automation stack. The self-hosting option provides guarantees that cloud-only platforms cannot match.

Make is a solid platform — genuinely good at what it does. But n8n's combination of open source, self-hosting, advanced features, and compelling economics makes it the default choice for serious automation work in 2026.

Try both. Build the same workflow in each. Feel the difference. Then make your choice.