n8n vs Make: An Honest Take After 80+ Client Automations

We've built over 80 production automations across both n8n and Make (formerly Integromat) for clients in healthcare, events, SaaS, and enterprise logistics. Both platforms are genuinely good. But 'genuinely good' doesn't mean interchangeable — and picking the wrong one for a project has real costs in time, money, and the 2am incident that wakes someone up. Here's what we've learned.

Where Make Wins: Speed and Simplicity for Standard Integrations

Make is exceptional when you need to connect well-supported apps quickly. Its visual scenario builder is the most intuitive in the market — a non-technical ops person can build and maintain a CRM-to-email sync without help from engineering. The pre-built module library is enormous, error messaging is clear, and the free tier is genuinely useful for low-volume use cases. For clients who need something working in days — not weeks — and are connecting apps that Make already supports natively, we still reach for Make first. It's the right tool for roughly 40% of the automation requests we see.

Where n8n Wins: Everything That Requires Real Engineering

n8n is a different animal. It's open-source, self-hostable, and exposes the full underlying data structure at every node. When we're building an AI agent that calls an LLM, parses the structured output, conditionally branches based on confidence scores, writes to a PostgreSQL database, and then triggers a webhook — that's n8n. The Code node (JavaScript or Python) means you're not fighting the platform's abstractions when you hit an edge case. For any automation that involves custom business logic, LLM calls, or data transformations that go beyond field mapping, n8n is materially faster to build on than Make.

The Cost Reality: It's Not What You Think

Make charges by operations (each module execution). For high-volume automations, that pricing model turns painful fast. A workflow that processes 50,000 records per month and touches 8 modules per record is 400,000 operations — that's Make's Teams plan or above. n8n Cloud charges by workflow executions, which is more predictable for complex multi-step workflows. But the real cost story is self-hosted n8n: for clients with engineering resources, a self-hosted n8n instance on a $40/month VPS handles unlimited executions. Three enterprise clients we work with run combined automation volumes that would cost $2,000–$4,000/month on Make, for under $200/month on self-hosted n8n.

Reliability: Where Both Platforms Have Blind Spots

Make's cloud reliability is excellent for standard scenarios, but the execution queue can back up during maintenance windows — a problem if your automation is time-sensitive. n8n Cloud has improved significantly in 2025 but still occasionally has webhook delivery delays. Self-hosted n8n is only as reliable as your infrastructure, which means you need proper queue management (we use Redis + n8n's queue mode) and monitoring. We've had Make scenarios silently fail due to API rate limit changes from third-party apps, and we've had n8n workflows break after minor version updates. Neither platform is fire-and-forget at scale.

Our Actual Decision Framework

• Use Make when: the integrations are standard, the client team needs to maintain it without dev support, and volume is under 50K operations/month
• Use n8n when: there's custom logic, LLM calls, database writes, or the client wants self-hosted control
• Use neither when: the workflow is truly mission-critical and real-time — that's a job for a custom service with proper error handling, retries, and dead-letter queues
• Consider both in parallel when: Make handles the simple high-volume tasks and n8n handles the complex logic layer

The 'n8n vs Make' debate misses the real question: what does this automation actually need to do, who will maintain it, and what breaks if it fails? At Kodesinc, we're platform-agnostic in the best sense — we use whichever tool delivers the most reliable outcome for that specific client workflow. If you're evaluating automation platforms for your business or need a team to build and maintain production-grade pipelines, we're happy to walk through your use case with no sales pressure.