Automation tools compared
n8n vs Make in 2026: which automation tool should you pick?
Pick n8n if you want to own the infrastructure and write custom logic. Pick Make if you want the fastest path from idea to working flow with no server to manage.
Both n8n and Make (formerly Integromat) let you connect apps and automate workflows without building each integration from scratch. The gap between them is philosophical: n8n is open-source and gives you control, Make is a polished hosted product that gives you speed. The right answer depends on who is building and where the workflow needs to run.
Side by side
| Factor | n8n | Make |
|---|---|---|
| Hosting | Self-host free, or n8n Cloud | Fully hosted only |
| Pricing model | Per execution on cloud, unlimited when self-hosted | Per operation (each step counts) |
| Custom code | First-class JavaScript and Python nodes | Limited, mostly no-code |
| Learning curve | Steeper, developer-friendly | Gentler, visual-first |
| Data residency | Full control when self-hosted | Vendor-controlled regions |
| AI agent nodes | Native LangChain and agent support | AI modules, less flexible |
Where n8n wins
If cost scales badly on Make because your flows have many steps, n8n self-hosted flips the economics: you pay for a server, not per operation. It also wins when you need custom code inside a workflow, when data cannot leave your infrastructure for compliance reasons, or when you are building AI agents that call tools, because its LangChain integration is genuinely deep. Teams with an engineer in the room tend to end up on n8n.
Where Make wins
Make wins on time to first working automation. The visual builder is more forgiving, the template library is larger, and a non-technical operator can ship a useful flow in an afternoon. If nobody on your team wants to manage a server or think about updates, Make removes that entire category of work. For marketing and operations teams without engineering support, that convenience is worth the per-operation pricing.
The honest recommendation
There is a third answer that most comparison articles skip: for anything beyond simple app-to-app plumbing, a purpose-built automation outperforms both. Visual tools are excellent for connecting five apps, but a workflow with branching logic, retries, and AI decisions becomes fragile as a spaghetti of nodes. At that point custom automation engineering pays for itself in reliability. Digiton builds on n8n when a visual layer helps the client maintain it, and drops to code when the logic demands it. Start with the tool your team can operate, and graduate when the workflow outgrows the canvas.
Frequently asked questions
What is the difference between n8n and Make in 2026?
n8n is open-source and self-hostable with first-class custom code and AI agent nodes, giving you control and predictable cost. Make is fully hosted, visual-first, and faster for non-technical teams, but prices per operation, which grows expensive as flows get complex.
Is n8n cheaper than Make?
Self-hosted n8n is far cheaper at scale because you pay for a server rather than per operation, so complex multi-step flows do not inflate the bill. Make can be cheaper at very low volume where a server feels like overkill and convenience matters more than unit cost.
Which is better for building AI agents, n8n or Make?
n8n, because of its native LangChain and agent tooling, which lets an agent call tools, branch on model output, and chain steps with real control. Make has AI modules but they are less flexible for genuine agentic workflows that need custom logic between model calls.
Related
Ready to put AI to work?
Book a discovery audit and we will map the highest-ROI AI agents and automations for your business.
Book a discovery audit →