Make vs n8n

Make and n8n are the two workflow automation tools GTM Engineers debate most. Both let you connect APIs, transform data, and build multi-step automations without (much) code. But they differ fundamentally: Make is a cloud-hosted visual platform with per-operation pricing. n8n is source-available and self-hostable with no per-execution limits. That architectural difference shapes everything from cost to control.

In our 2026 survey, n8n hit 54% adoption among GTM Engineers, up from under 30% a year ago. Make holds steady at around 35%. Zapier, once the default, has fallen to third among technical users. The trend is clear: GTM Engineers prefer tools that give them more control and lower marginal costs at scale.

This comparison breaks down the real trade-offs between Make's polished cloud experience and n8n's self-hosted power. We'll cover the scenarios where each tool wins and why most GTM Engineers are moving toward n8n.

Feature Comparison

Where Make Wins

Make's visual builder is the best in the automation market. Modules snap together with drag-and-drop, data mapping is visual (you can see the JSON structure and click to map fields), and the execution log shows exactly what happened at each step. For building and debugging automations, Make's UX is faster than n8n's, especially for complex multi-branch workflows.

Integration count matters when you're connecting niche tools. Make has 1,800+ pre-built modules compared to n8n's 400+. If you're integrating with a lesser-known CRM, project management tool, or analytics platform, Make is more likely to have a native connector. n8n's community nodes help close the gap, but Make's library is broader.

Error handling in Make is more intuitive. You can create error routes that catch failures at specific modules and route them to alternate paths, retry logic, or error notification workflows. n8n has error handling, but Make's visual approach makes it easier to build resilient automations without deep technical knowledge.

For teams with mixed technical levels (GTM Engineer + non-technical marketing ops), Make's interface is accessible to everyone. Building and maintaining automations doesn't require the GTM Engineer to be the single point of failure. n8n's interface is good but skews more technical.

Where n8n Wins

Cost at scale is n8n's decisive advantage. Self-hosted n8n costs $0 in software fees. Run it on a $10/month VPS and execute millions of operations per month with zero marginal cost. Make's Pro plan ($16/month) gives you 10,000 operations. A single enrichment waterfall run on 5,000 leads could blow through that in one execution. The math is simple: if you run more than 10,000 operations per month, n8n saves money. Most GTM Engineers run far more than that.

Data sovereignty is non-negotiable for some teams. With self-hosted n8n, your data never leaves your infrastructure. Contact data, enrichment results, CRM syncs, and email content all flow through your own servers. Make routes everything through their cloud. If you're handling sensitive prospect data or your security team has data residency requirements, n8n is the answer.

Python support in code nodes is a differentiator for GTM Engineers. Make only supports JavaScript in code modules. n8n supports both JavaScript and Python. Since Python is the dominant language for data processing, enrichment scripts, and API integrations in the GTM stack, n8n's Python support means you can reuse existing scripts directly in your workflows.

Git-based version control lets you treat workflows as code. Export workflows as JSON, commit them to a repo, create branches for testing, and roll back to previous versions. This is how software engineers manage configuration, and it's how GTM Engineers should manage automation logic. Make's version history is limited to scenario-level snapshots with no branching.

The self-hosted architecture means you control uptime, scaling, and infrastructure. No dependency on Make's SaaS availability. During Make's outages (which happen quarterly), self-hosted n8n users are unaffected.

Pricing Breakdown

Make pricing: Free (1,000 ops/month), Core ($9/mo for 10,000 ops), Pro ($16/mo for 10,000 ops + advanced features), Teams ($29/mo per user for 10,000 ops), Enterprise (custom). Extra operations cost $9 per 10,000. A GTM team running 100,000 operations per month on Pro: $16 + $81 (90K extra ops) = $97/month. At 500,000 ops: $457/month.

n8n cloud pricing: Starter ($20/mo for 2,500 executions), Pro ($50/mo for 10,000 executions), Enterprise (custom). n8n cloud counts executions (workflow runs), not individual operations. One workflow with 10 steps counts as 1 execution, not 10. This makes n8n cloud significantly cheaper than Make at equivalent workflow complexity.

n8n self-hosted: Free. Run it on a $5-$20/month VPS (Hetzner, DigitalOcean, or your existing infrastructure). No execution limits. The total cost is your server bill. A $10/month VPS handles most GTM automation workloads. That's $120/year vs Make's $1,164/year (Pro at 100K ops/month) or more. The self-hosted option is why n8n adoption is accelerating among GTM Engineers who can manage a basic Linux server.

The Verdict

Use Make if you value the best visual builder in the market, need broad integration coverage (1,800+ modules), and prefer cloud-hosted simplicity. Make is the right choice for teams with mixed technical levels where non-engineers need to build and maintain automations. If your operation volume stays under 50,000 ops/month, Make's pricing is reasonable.

Use n8n if you run high-volume automations (100K+ operations/month), care about data sovereignty, want Python support, or prefer infrastructure you control. n8n is the technical operator's choice, and at 54% adoption among GTM Engineers, it's becoming the default for a reason. Self-hosting eliminates per-operation costs and gives you full control.

The market is moving toward n8n. The 54% adoption figure tells the story. GTM Engineers are technical users who optimize for cost, control, and flexibility. n8n delivers all three. Make remains excellent for its target audience (visual-first automation users), but that audience increasingly overlaps less with the GTM Engineer profile.

Frequently Asked Questions

Is n8n hard to self-host?

No. n8n provides Docker images and one-click deploys for major cloud providers. A GTM Engineer with basic Linux skills can set up n8n on a VPS in under an hour. The community has extensive guides. If you can configure a Clay workflow, you can self-host n8n.

Can Make handle enterprise-scale automations?

Yes, but the cost scales linearly with volume. Enterprise plans provide higher operation limits and priority support. For high-volume use cases (millions of ops/month), Make works but costs significantly more than self-hosted n8n.

Which integrates better with Clay?

Both work well with Clay via HTTP/webhook nodes. Make's HTTP module is slightly more visual for configuring API calls. n8n's HTTP node is more flexible with code-based request customization. The difference is marginal. Pick based on other factors.

Can I migrate workflows from Make to n8n?

There's no direct migration tool. You'd need to rebuild workflows manually. The concepts translate (modules map to nodes, data mapping is similar), but the actual configuration doesn't port. Plan for 1-2 hours per workflow for migration.

Does n8n cloud have the same benefits as self-hosted?

n8n cloud gives you the same features without server management, but you lose the cost advantage (cloud pricing is per-execution) and data sovereignty (data transits n8n's infrastructure). For most GTM Engineers, self-hosted is the way to go. Use cloud if you don't want to manage a server.