Windmill vs n8n: Which Automation Platform Fits Your Team?

Choose Based on Your Team

The best way to choose between these two is simple: answer one question.

Does your team think in code or in workflows?

If your team is mostly marketing, operations, or non-technical builders, n8n wins. The visual canvas is faster to learn. Pre-built nodes handle 90% of SaaS integrations (Slack, Gmail, Salesforce, HubSpot, Notion, etc.) without writing a line of code.

If your team is engineers or data people who prefer scripts over clicks, Windmill wins. Write Python or TypeScript. Import any npm or PyPI package. Compose scripts into workflows. Deploy as APIs or internal apps. Full version control with Git sync.

This is not about which platform is better: it is about which one matches how your team already works. Switching later is possible but costly (more on that below).

For mixed teams (some coders, some ops people), n8n is visual canvas tends to win because non-technical teammates can operate it independently. Windmill works too, but requires ops to write or approve all scripts.

The Cost Difference: Per-Execution vs Per-Seat

n8n charges by execution volume. Windmill charges by number of developers.

n8n pricing starts at $20/month on cloud for a base execution allowance. The Business tier (self-hosted) is 667 euros/month for 40,000 executions/month. If your workflows are bursty and unpredictable—lots of executions some days, few others—this model makes budgeting hard.

Windmill pricing starts at $10/month per developer on cloud, plus optional Compute Units (workers). If you have 5 developers, that is $50/month baseline. Easier to predict and cap.

For a team of 10 running automation at scale:

• n8n: Budget 667 euros+ monthly for self-hosted, or purchase a higher execution plan on cloud
• Windmill: Budget $100+ monthly ($10 per developer) plus per-worker costs

Windmill is more transparent if you know your team size upfront. n8n is cheaper for small teams with low execution volume. Both offer free tiers for small projects or testing.

Neither platform's cloud is dramatically expensive—the difference is in predictability. Pick based on whether you prefer a fixed headcount cost or a variable execution cost.

Vendor Lock-In: A Real but Different Risk for Each

n8n lock-in is subtle. You build workflows using pre-built nodes. Those nodes are n8n-specific. If you exit n8n, you rewrite every workflow in your chosen replacement platform. Not a literal code rewrite, but a workflow rewrite. This is expensive.

Windmill lock-in is lower. You write in standard languages (Python, TypeScript). Your scripts are portable—you could run them outside Windmill if needed. The workflows (compositions of scripts) are Windmill format, but your core logic is standard code.

This matters if you expect to migrate platforms later. European companies sensitive to vendor lock-in often prefer Windmill for this reason.

GDPR and Data Residency

Both platforms support self-hosting on your infrastructure. n8n is fair-code (source-available, restrictive commercial use license). Windmill is AGPLv3 (true open-source, allows any commercial deployment).

If you need German or EU data residency with full compliance control, both work. With Windmill, you have cleaner commercial licensing (AGPLv3). With n8n, self-hosting is available but the fair-code license may restrict third-party hosted offerings.

For organizations running on-prem or EU infrastructure, Windmill is simpler from a licensing perspective.

AI Workflows: Pre-Built vs Flexible

n8n has native nodes for OpenAI, Anthropic Claude, vector databases, and AI agents with tool use. Drag a Claude node onto the canvas. Connect it to your data. Done. No coding required.

Windmill has no pre-built AI nodes. But you can import any Python library: LangChain, HuggingFace, Anthropic SDK, etc. Build anything. More flexible, but requires coding.

For simple AI tasks (summarize email with Claude, extract text with GPT, generate images with DALL-E), n8n is faster. For complex AI pipelines (multi-step reasoning, fine-tuned models, agent loops), Windmill's Python ecosystem gives you more options.

Example from testing: Building an email triage bot (Gmail → AI summary → Google Sheets + Slack). n8n is pre-built Gmail and Claude nodes made this faster. Windmill would require custom Gmail API integration code, but the Python workflow would be more customizable.