n8n vs Make (Integromat) 2026 Guide

TL;DR

n8n is the pick for technical teams and self-hosters — unlimited workflows on your own server, JavaScript and Python code nodes in every step, and a fair-code license that keeps you in control. Make (formerly Integromat) is the pick for visual thinkers and non-developer teams — its canvas-style scenario builder is unmatched for mapping complex branching logic, and 1,000 free operations/month is the most generous free tier in the space. The core tradeoff: n8n self-hosted = no per-execution billing ever; Make = pay-per-operation at scale, but significantly easier for non-developers to master without training.

Quick Comparison

	n8n	Make (Integromat)
Free tier	Self-hosted (unlimited)	1,000 ops/month (cloud)
Entry paid (cloud)	$20/mo (2,500 executions)	$9/mo (10,000 ops)
Self-hostable	Yes — Docker, community edition	No
License	Fair-code (source available)	Proprietary SaaS
App integrations	400+ native nodes	1,500+ apps
Code steps	Yes — JavaScript and Python	Built-in formula functions
Visual builder	Node graph canvas	Flowchart canvas
Webhook support	All plans	All plans
Pricing model	Per workflow execution	Per operation (each module run)
Offline / self-hosted	Full featured	Not available

Pricing Model: The Key Difference

This is where n8n and Make diverge most sharply, and it's worth understanding before anything else.

Make charges per operation. Every module run in a scenario counts as one operation. A scenario that pulls from Google Sheets (1 op), transforms data with a text function (1 op), and posts to Slack (1 op) costs 3 operations per trigger. Process 500 records in a batch and you're at 1,500 operations for a single execution of that scenario. The free plan covers 1,000 operations/month — which sounds generous until a data-heavy scenario burns through it in a single afternoon. The Core plan at $9/month gives 10,000 ops; Pro at $16/month gives 10,000 ops with higher data transfer; Teams at $29/month adds multi-user collaboration. For high-volume data workflows, operation costs accumulate quickly.

n8n charges per workflow execution. It doesn't matter if your workflow has 3 nodes or 30 — one trigger fires = one execution counted. The Cloud Starter plan at $20/month covers 2,500 executions with up to 5 active workflows. Cloud Pro at $50/month covers 10,000 executions and unlimited active workflows. But the real n8n value proposition is self-hosting: run n8n on your own VPS or server and you pay nothing per execution — only your infrastructure costs. A $10/month DigitalOcean or Hetzner instance running n8n covers unlimited workflows permanently.

For teams with moderate to high data volumes (thousands of records per day), n8n self-hosted is dramatically cheaper than Make at scale. For teams with simple, low-frequency automations, Make's $9/month Core plan often covers everything needed with no infrastructure overhead.

Integration Ecosystem and Node Quality

Make's 1,500+ app integrations outpace n8n's 400+ native nodes by a wide margin, and this matters in practice. If you need to connect a niche SaaS tool — a specific email platform, a regional payment processor, an industry-specific CRM — Make is significantly more likely to have a native connector ready to configure.

That said, n8n's smaller native integration count is substantially offset by the HTTP Request node and Code node. The HTTP Request node connects to any REST or GraphQL API with OAuth, API key, or basic auth support — most modern SaaS tools with a public API become accessible without a dedicated integration. The Code node lets you write JavaScript or Python that runs server-side in any workflow step, covering anything the node library doesn't.

Make's module quality is generally high and consistent. Each integration has rich field mapping, proper error handling, and OAuth refresh token management built in. n8n's native nodes vary in depth — some are comprehensive (GitHub, HubSpot, PostgreSQL, Notion) and others are simpler pass-throughs. For non-developers who need to configure an integration without writing any code, Make's polished module UI is genuinely easier. For developers who write custom logic anyway, n8n's flexibility is the better foundation.

Both platforms support webhooks on all plans and handle scheduled polling for trigger-based automations. Make's scheduled scenario triggers have a cleaner UI for configuring intervals; n8n's cron-expression trigger is more flexible for complex schedules but requires knowing cron syntax.

Builder Experience: Visual Canvas vs Node Graph

Make's visual scenario canvas is its signature feature. You see your entire automation as a flowchart — data flowing from left to right, router modules branching the flow into parallel paths, aggregator modules collecting results back together. The interface updates in real-time as you add modules, and the data mapping panel shows all available fields from previous modules with type-aware autocomplete. When debugging a complex multi-path scenario, you can click any module to inspect its input and output data. It's one of the most intuitive automation UIs available.

n8n uses a node-graph model: nodes appear on a grid canvas connected by edges. The mental model is closer to Apache Airflow or Node-RED than to a flowchart. For developers familiar with pipeline tools or directed acyclic graph concepts, n8n's canvas is immediately familiar. For non-developers, Make's flowchart usually clicks faster in the first hour.

Where n8n's builder decisively wins is the Code node — drop into JavaScript or Python at any point in your workflow to transform data, call APIs with custom logic, or handle edge cases that no connector covers. Make has built-in formula functions and some text/number transformation tools, but there's no arbitrary code execution. For developer-adjacent automation — the kind where you need to reshape API responses, calculate derived fields, or implement custom business logic — n8n's code support makes it significantly more capable.

Error handling is robust in both platforms. Make lets you attach error handlers directly to individual modules, define fallback paths, and configure rollback behavior. n8n has error workflow triggers — when a workflow fails, you can route the failure into a separate error-handling workflow that sends an alert, logs the error, or retries with modified parameters. Both approaches are production-grade; Make's is more visual, n8n's is more code-oriented.

Self-Hosting: n8n's Decisive Advantage

n8n self-hosting is a first-class deployment target. The community edition is freely available on GitHub, ships as an official Docker image, and runs on any Linux VPS, AWS EC2, Railway, Render, or on-premises server. Documentation covers deployment on every major platform, including Kubernetes with Helm charts for larger operations.

# Docker quickstart for n8n self-hosted
docker run -it --rm \
  --name n8n \
  -p 5678:5678 \
  -v ~/.n8n:/home/node/.n8n \
  n8nio/n8n

For production, n8n recommends PostgreSQL as the backing database (SQLite works for development) and a reverse proxy (nginx or Caddy) for HTTPS termination. Queue mode with Redis enables parallel workflow execution for high-throughput workloads. The total infrastructure cost for a productive n8n self-hosted setup: $10–20/month on a basic VPS.

Make has no self-hosted option. This is a hard blocker for regulated industries (healthcare, financial services), organizations with data residency requirements, and teams handling sensitive internal data that cannot transit third-party infrastructure. n8n's fair-code license (Sustainable Use License for cloud, source available for inspection) also means security teams can audit the codebase — critical for enterprise security reviews.

For teams that want managed cloud without self-hosting, n8n Cloud at $20/month is still cheaper than Make's Teams plan ($29/month) for equivalent execution volumes, and it supports more simultaneous active workflows at the Pro tier.

When to Use Which

Choose n8n when:

• Your team includes developers or is comfortable with basic server maintenance
• You process high data volumes where per-operation pricing compounds quickly
• Data sovereignty is required — no third-party cloud for workflow data or logs
• You need JavaScript or Python code execution inside workflow steps
• Budget is a constraint — self-hosting eliminates execution costs entirely

Choose Make when:

• Your automation team is primarily non-technical (ops, marketing, sales)
• You want the most polished visual canvas builder with minimal setup
• You need one of Make's 1,500+ app connectors not natively available in n8n
• You prefer a managed SaaS platform with no infrastructure overhead
• Your operation volume is low-to-moderate (under 40,000 ops/month on the Core or Pro tier)

For teams replacing Zapier, both n8n and Make are strong alternatives — see the Zapier alternatives roundup 2026 for a full comparison across more platforms including Activepieces and Pabbly Connect. If you're building automations that feed into form capture workflows, Typeform alternatives 2026 covers the form-to-webhook pipeline side. For teams building internal dashboards alongside their automations, Retool vs Appsmith vs Budibase 2026 covers the low-code internal tools that connect to the same data sources.

The bottom line: n8n rewards technical investment with long-term cost savings and maximum flexibility. Make rewards non-technical users with a best-in-class visual experience and the broadest integration catalog in the automation market. Most engineering teams self-hosting n8n never reconsider; most ops teams on Make's visual canvas never look back either.