n8n vs Make: The Complete 2026 Comparison for Workflow Automation

If you're weighing n8n vs Make for workflow automation, here's the short version: n8n is the stronger pick for technical teams that want self-hosting, code-level control, and predictable costs at scale. Make fits non-technical teams that need quick setup and lots of pre-built integrations without touching infrastructure. The longer answer depends on your workflow complexity, budget trajectory, data sovereignty needs, and whether you plan to build AI agents. This n8n vs Make comparison covers every dimension that shapes the decision.

Background: What Are n8n and Make?

n8n (short for "nodemation") is a fair-code-licensed workflow automation platform founded in 2019 by Jan Oberhauser in Berlin. Its source code is public on GitHub with over 200,000 stars. You can self-host it via Docker or use n8n Cloud. The company has raised over $240 million in announced funding at a $5.2 billion valuation, following a strategic investment from SAP in May 2026.

Make (formerly Integromat) is a cloud-only visual automation platform founded in 2012 in Prague by Ondrej Gazda, Patrik Simek, and four other co-founders. It grew bootstrapped to $10 million in revenue before Celonis acquired it in 2020 for over $100 million. The Integromat-to-Make rebrand happened in February 2022, and the platform now serves over 400,000 organizations.

Both solve the same core problem: connecting apps and automating multi-step workflows without (or with minimal) code. They differ in how.

n8n vs Make: Feature Comparison Table

| Feature | n8n | Make | |---|---|---| | Deployment | Self-hosted (Docker) or cloud | Cloud-only SaaS | | Licensing | Fair-code (Sustainable Use License) | Proprietary | | Billing model | Per workflow execution | Per credit/operation | | Free tier | Community Edition (unlimited, self-hosted) | 1,000 credits/month | | Integrations | 400+ native nodes (plus 600+ community node packages) | 3,500+ native | | Code nodes | JavaScript and Python on all plans | Make Code app (JS/Python) on all paid plans; reusable Custom Functions on Enterprise only | | AI agents | LangChain-based, RAG, multi-model, MCP | AI Agents with sub-agents, Make Grid, Maia assistant | | Self-hosting | Yes (Docker, on-prem, air-gapped) | No | | Security certs | SOC 2 Type II, SOC 3 | SOC 2 Type II, SOC 3, ISO 27001 | | Sub-workflows | Yes (reusable sub-workflows) | Yes (subscenarios via Call a Scenario module) |

Pricing: The Make vs n8n Cost Equation

Pricing is where the make vs n8n decision gets real. The two platforms bill in fundamentally different ways.

n8n charges per workflow execution. A workflow with 3 steps and one with 200 steps both count as a single execution. The self-hosted Community Edition is free with unlimited executions. You only pay for hosting, roughly $5-25/month on a VPS. Cloud plans start at EUR 24/month (EUR 20/month billed annually) for 2,500 executions.

Make charges per credit. Each module (step) in a scenario consumes at least one credit. A 5-module scenario running 5,000 times per month burns 25,000+ credits. The free tier gives you 1,000 credits/month. Paid plans start at $9/month (Core, 10,000 credits) and go up to $29/month (Teams).

What This Looks Like at Scale

At low volume, Make can actually be cheaper. A simple two-step automation running a few hundred times a month fits comfortably in Make's free tier. Costs diverge fast once workflows grow in complexity, though.

Take a 20-step workflow running 2,500 times per month. On n8n, that's 2,500 executions regardless of step count. On Make, that's 50,000 credits minimum, well beyond the Core plan's 10,000 credit allocation.

Make also moved from operations-based to credits-based pricing in August 2025, a change that's generated ongoing discussion among users. Non-AI operations cost 1 credit each, but AI operations vary by token usage. Harder to predict.

n8n Plan Breakdown

| Plan | Price (monthly / annual) | Executions | Key Features | |---|---|---|---| | Community (self-hosted) | Free | Unlimited | All integrations, code nodes | | Registered Community | Free | Unlimited | Adds folders, debug-in-editor, custom execution data | | Cloud Starter | EUR 24/mo (EUR 20 annual) | 2,500 | Managed hosting, unlimited workflows | | Cloud Pro | EUR 60/mo (EUR 50 annual) | 10,000 | Priority support, unlimited workflows | | Business (self-hosted) | EUR 800/mo (EUR 667 annual) | 40,000 | SSO/SAML, LDAP, Git version control |

Self-Hosting and Data Sovereignty

This one's binary. n8n supports self-hosting. Make does not.

For teams in regulated industries (healthcare, finance, government), keeping data on your own infrastructure isn't optional. n8n runs on-premise, in a private cloud, or air-gapped. The Community Edition has no execution limits when self-hosted.

Getting n8n Running with Docker

n8n offers a one-line install that sets up the full stack (and from n8n 3.0, this becomes the only supported installation method, replacing npm):

curl -fsSL https://get.n8n.io | sh

This creates a Docker Compose setup at ./n8n/compose.yml and starts n8n at http://localhost:5678. Prerequisites are Docker and the Docker Compose v2 plugin on Linux or macOS.

For more control, you can run n8n directly with Docker:

docker volume create n8n_data
docker run -it --rm --name n8n \
  -p 5678:5678 \
  -v n8n_data:/home/node/.n8n \
  docker.n8n.io/n8nio/n8n

For production deployments, you'll want a reverse proxy with TLS and a PostgreSQL backend instead of the default SQLite:

docker run -it --rm --name n8n \
  -p 5678:5678 \
  -e DB_TYPE=postgresdb \
  -e DB_POSTGRESDB_HOST=your-db-host \
  -e DB_POSTGRESDB_DATABASE=n8n \
  -e DB_POSTGRESDB_USER=n8n \
  -e DB_POSTGRESDB_PASSWORD=your-password \
  -e N8N_ENCRYPTION_KEY=your-custom-key \
  -e N8N_SECURE_COOKIE=true \
  -v n8n_data:/home/node/.n8n \
  docker.n8n.io/n8nio/n8n

Minimum specs for a basic deployment: 2 CPU cores, 2 GB RAM, 20 GB storage. Production workloads typically need 4 GB or more RAM, especially when running PostgreSQL alongside n8n. Back up the encryption key. If you lose it, existing credentials can't be decrypted.

Make requires no setup at all. Sign up at make.com, build scenarios in the browser, and activate them. The tradeoff: your data lives entirely on Make's infrastructure. Make holds SOC 2 Type II, SOC 3, and ISO 27001 certifications, which satisfy many compliance frameworks. Still, no managed service can match the data sovereignty guarantees of running things yourself.

AI Agent Capabilities

Both platforms offer AI features now, but the architectures and depth differ significantly.

n8n provides native AI agent nodes built on LangChain. You get multi-model flexibility (OpenAI, Anthropic, Google, self-hosted models via Ollama), RAG with vector databases, Model Context Protocol (MCP), and tool use with human-in-the-loop approvals. All of this works on every plan, including the free Community Edition. Over 80% of workflows on n8n now involve AI agents, according to company reporting.

Make offers AI Agents with goal-setting, reasoning visibility, and sub-agent support. Make Grid lets you visualize and coordinate multi-agent automation landscapes. An AI assistant called Maia builds scenarios from natural-language prompts. Make also supports MCP Server integration. AI operations use a credit-based token pricing model with separate input/output token rates.

For teams choosing between n8n or make specifically for AI workflows, n8n has a clear depth advantage. Its code nodes let you write arbitrary JavaScript or Python logic around AI calls, and you can chain agents with sub-workflows. Make's Code app allows JavaScript and Python on all paid plans, but reusable Custom Functions are locked to the Enterprise plan.

Ease of Use and Integrations

Make wins on initial onboarding. Its visual builder is more polished for non-technical users, the scenario templates get you running quickly, and 3,500+ native integrations mean most SaaS tools come pre-wired. Expect a 2-4 week ramp to production-ready workflows.

n8n's node-based visual editor is powerful but assumes more technical comfort. The integration count sits around 400+ native nodes, supplemented by 600+ community-built node packages. Gaps in native integrations can be filled with HTTP/webhook nodes or custom code, but that takes a developer.

Both platforms support conditional branching, error handling, and webhook triggers. Make uses "scenarios" and "modules"; n8n uses "workflows" and "nodes." Same concepts, different labels.

When to Choose n8n or Make

Choose n8n if:

• You need self-hosting for data sovereignty or compliance
• Your workflows have many steps (per-execution billing saves money)
• You want native code nodes (JavaScript/Python) on every plan
• AI agent depth matters: RAG, multi-model, tool use
• You have engineering resources to manage infrastructure

Choose Make if:

• Your team is non-technical and needs fast visual setup
• You rely on a wide variety of SaaS tools with pre-built connectors
• You prefer managed infrastructure with zero DevOps
• Your workflows are simple (few steps) and low volume
• SOC 2 + ISO 27001 managed compliance covers your requirements

Some teams run both. Make handles front-end marketing and ops automations where ease of use matters. n8n handles backend logic, AI agents, and data-sensitive workflows. You can connect them via authenticated webhooks.