So, on my last newsletter (if you’ve not joined me there, do it now, it’s free 😉), many people commented that they liked the n8n vs Zapier blog, but they’re stuck between n8n vs Make. They’ve heard of these three tools and aren’t sure which way to go. I could guess why – there’s a lot of overlap and marketing noise. So I went full agent mode: I dug into Make, read the docs, tested features, and built a few flows. In this post, I’ll share what I found. Unlike my last story‑driven post, this one is a product comparison with a personal touch. Hopefully, it will help you decide which platform is right for your automation needs.
What sets n8n and Make apart?
The core difference comes down to control versus convenience. n8n is an open‑source automation platform that you can self‑host or use as a cloud service. Each run of a workflow counts as a single execution regardless of how many steps it contains. You can drop in JavaScript or Python code, use built‑in nodes, connect to any REST API via an HTTP request node, and even scale horizontally with queues. You own the data and can modify the source if you need to.
Make (formerly Integromat) is a fully hosted integration platform. It uses a flowchart‑style editor where each module (an action like “fetch a record” or “send an email”) counts as an operation toward your monthly quota. It’s designed for non‑technical users who want to visually connect apps. You get thousands of pre‑built modules, routers for branching logic, iterators for arrays and aggregators, and error‑handling routes. The cost of a scenario scales with the number of operations.
If you’re technical and want to treat automation like an application you own, n8n’s flexibility is appealing. If you want to build quickly without writing code and are comfortable with a hosted service, Make’s user‑friendly environment may suit you better.
Quick comparison: n8n vs Make
Below is a high‑level look at how the two tools differ. The cells use short phrases and avoid long sentences, so you can scan them quickly.
| Factor | n8n | Make |
|---|---|---|
| Hosting | Self‑host or cloud | Cloud only |
| Pricing unit | Execution per workflow | Operations/credits per module |
| Integrations | 400–1,000+ nodes + HTTP | 2,000+ modules |
| Custom code | JavaScript & Python included | Flowchart with routers & iterators |
| Visual editor | Node‑based canvas | Flowchart with routers & iterators |
| AI & agents | Native AI nodes & agents | Pre‑built AI modules & assistant |
| Best fit | Developers & data‑heavy workloads | Non‑technical users & quick setups |
Hosting and data control
n8n: You can install n8n on your own server or run it in the cloud. Self‑hosting means data stays on your infrastructure. Developers can write custom nodes or modify source code because n8n is open-source. For teams that can’t use public SaaS due to compliance or data‑residency requirements, this is a huge advantage.
Make: Everything runs in Make’s cloud. It offers an on‑premise agent that allows secure connections to private databases, but the scenarios still execute in the cloud. You don’t manage servers or upgrades, but you also don’t control the runtime environment.
Pricing models
n8n charges by workflow execution when you use n8n Cloud. A run with one step or fifty steps counts as one execution. The Starter plan includes roughly 2,500 executions per month for around $20 (billed annually), while the Pro plan offers about 10,000 executions for around $50. Self‑hosting n8n is free; you only pay for your server, so the cost scales with infrastructure, not usage.
Make price plans based on operations (credits). Each module action in a scenario consumes one credit. The free plan includes 1,000 credits per month and limits runs to every 15 minutes. The Core plan costs about $9/month and provides 10,000 credits. The Pro and Teams tiers offer more credits and collaboration features. Because every operation counts, scenarios with loops or complex logic can consume many credits, increasing your costs. Make recently replaced “operations” with “credits,” but the concept is the same.
Integrations and extensibility
n8n includes hundreds of official nodes and unlimited HTTP integrations. You can hit any REST API using the HTTP Request node and write JavaScript or Python for custom logic. The community builds and shares additional nodes, so the ecosystem keeps growing. All integrations are free to use, even on the free self‑hosted edition blog.promptlayer.com.
Make ships with over two thousand modules for popular SaaS apps. You can build custom connectors through a developer portal, but code blocks are only available on higher‑tier plans. For most business tools, Make’s library covers what you need, and the visual editor lets you map fields without writing expressions.
Logic and developer experience
In n8n, you build workflows by linking nodes on a canvas. You can branch, loop, and combine sub‑workflows for reuse. A built‑in Function node lets you write JavaScript or Python to transform data or call external APIs. Developers can also create error workflows that catch failures and implement retries or notifications. Because of this, n8n feels like a programmable runtime—you have fine‑grained control and can scale with queues and workers if needed.
In Make, workflows are called scenarios. Each module acts, and routers handle conditional branches. Iterators and aggregators loop through arrays, while error handlers specify whether to stop, ignore, or retry when something fails. It’s highly visual: you drag modules into a flowchart, connect them, and map outputs to inputs using forms. Make abstracts away much of the complexity but offers less control over custom logic and error handling unless you’re on enterprise plans.
AI and intelligent automation
n8n has embraced AI. It offers AI Agent nodes that let language models call other nodes as tools, support for LangChain nodes, retrieval‑augmented generation via vector databases, and integration with local models like Ollama. Because you can write code anywhere in the workflow, you can integrate any model provider that exposes a REST API.
Make focuses on plug‑and‑play AI modules. There are pre‑built connectors for OpenAI, DALL‑E, Whisper, Google Vision, ElevenLabs, and others. Make’s AI Assistant suggests automations in natural language, and its emerging AI Agent feature allows adaptive multi‑step workflows. These options are great for business users, but may limit flexibility compared with writing your own code.
Ease of use and learning curve
n8n requires more technical knowledge. Its expression editor uses JSON syntax, and understanding inputs/outputs pays off once workflows become complex. The reward is an environment that scales with your skills—sub‑workflows, branching, error handling, and code make it powerful for engineers.
Make is easier to start with. The drag-and-drop editor, built-in functions, and templates help you get up and running quickly. Visual mapping and form‑based configuration mean you don’t need to know code. For many teams, that’s exactly what they need.
Who should choose which?
Choose Make if you want a quick start, don’t need to self‑host, and prefer a simple UI. It’s great for marketing teams, operations staff, freelancers and agencies that value ease of use and a large app library. The credit‑based pricing is predictable for small scenarios and you get built‑in error handling and scheduling.
Choose n8n if you need data control or plan to build complex workflows. Developers and technical teams will appreciate the ability to self‑host, write code, create sub‑workflows, and handle errors programmatically. The execution-based pricing on n8n Cloud is fair for multi-step flows, and self-hosting can be cost-efficient at scale.
In case you’re choosing n8n, here’s the deployment guide for you:
Conclusion
After digging into both platforms, the choice really depends on your priorities. If you value convenience, drag‑and‑drop simplicity, and a wide selection of ready‑made integrations, Make delivers a polished, business‑friendly experience. If you need control, scalability, and the freedom to customize every step—including writing your own code—n8n offers a more flexible foundation. Both platforms continue to evolve with AI features and new connectors, so whichever you choose, you’ll be riding a wave of innovation in automation.
Frequently asked questions
What is the biggest difference between n8n and Make?
The largest gap is in control and pricing. n8n lets you self‑host and charges per workflow run, while Make is cloud‑only and charges per module operation.
Does n8n support as many integrations as Make?
Make has a larger library of pre‑built modules (over 2,000), but n8n connects to hundreds of services and can integrate with any REST API via its HTTP Request node.
Can I write code in Make?
Only on enterprise‑level plans. n8n includes JavaScript and Python Function nodes on all plans and even in the self‑hosted edition.
Which platform is cheaper?
For small, simple workflows Make’s low‑tier plans are inexpensive (e.g., $9 for 10k credits). For larger or more complex automations with loops, n8n’s single‑execution pricing can be more cost‑effective, especially if self‑hosted.
Who should self‑host n8n?
Organizations with strict compliance requirements, developers wanting full data control, or teams running high‑volume workflows will benefit from hosting n8n on their own infrastructure.
How is AI supported in each tool?
n8n offers AI Agent nodes, LangChain integration, and support for local models. Make includes ready‑made AI modules (OpenAI, Google Vision, etc.) and an AI assistant that suggests flows.
