# n8n vs Make: which one should you use to automate your business? > n8n vs Make compared: pricing, self-hosting, AI nodes, learning curve and integrations. Which automation tool fits your business, with clear picks. URL: https://gradual.pro/en/blog/n8n-vs-make Updated: 2026-09-29 - Make is easier to start with and has more native integrations; n8n gives more control and can run on your own server. - Make charges per operation (every step of every run); n8n charges per complete workflow execution, or nothing if you host it yourself. - For long workflows, high volume or sensitive data, n8n usually costs less and fits GDPR requirements better. - For non-technical teams with simple workflows, Make is usually the more comfortable choice. n8n and Make are two platforms for automating tasks between applications with a visual editor. The main difference is control: **Make is easier to start with and runs only in the cloud**, while **n8n can be installed on your own server, charges per complete execution and leaves more room for complex logic and AI**. If your team is not technical and your flows are short, Make usually fits better. If you handle volume, sensitive data or AI agents, n8n usually wins. Below you get the point-by-point comparison and the cases in which we would pick each one. ## What are n8n and Make? ### n8n n8n started in Berlin in 2019, founded by Jan Oberhauser. Its code is public under a fair-code model: you can install and use it for free in your company, but not resell it as a service without an agreement. It has a cloud version (n8n Cloud) and a self-hosted version. For a short definition, see the [n8n glossary entry](/en/glossary/n8n). ### Make Make was called Integromat until 2022. The company, of Czech origin, was acquired by Celonis and changed its name when it relaunched the product. It is a cloud-only service with a polished visual editor in which workflows are called "scenarios" and each step is a "module". ## n8n vs Make comparison table | Criterion | n8n | Make | |---|---|---| | Pricing model | Per complete workflow execution (Cloud); no license if you self-host the Community edition | Per operation: every module that runs uses one unit | | Self-hosting | Yes, on your server or the cloud you choose | No, only on Make's cloud | | Open source | Fair-code (public code, commercial use with limits) | No, proprietary | | AI nodes | Agent nodes, memory, tools and vector databases (built on LangChain) | Modules for the main AI models and agent features | | Learning curve | Medium-high: more technical | Low-medium: very visual | | Native integrations | Several hundred, plus any API through the HTTP node | Several thousand apps, plus any API through the HTTP module | | Code inside the flow | JavaScript and Python | Limited; Make's own functions | | Error handling | Error workflows, retries and a log of every execution | Per-module error handlers and execution logs | Integration counts are approximate and change every month. What matters is whether the applications you use have a connector or at least an API. ## How do n8n and Make pricing compare? The charging model is the factor that changes your bill the most over time. ### How does Make charge? Make charges per **operation**: every time a module runs, it uses one. A 10-module scenario that processes 100 invoices a day uses about 1,000 operations daily. Plans include a set number of operations per month, and if you go over, you buy more. With short flows and low volume, this is cheap. The problem appears as flows grow: loops over lists, transformation steps and checks add operations on every pass. ### How does n8n charge? n8n Cloud charges per **workflow execution**: the whole flow counts as one, whether it has 3 nodes or 30. And if you self-host the Community edition, there is no license cost: you pay for the server and its maintenance. ### Example with round numbers Picture a flow that processes 3,000 orders a month and has 15 steps. - In Make, that is about 45,000 operations a month. - In n8n Cloud, it is 3,000 executions. - In self-hosted n8n, the cost depends on the server, not on volume. We do not quote exact prices because both vendors change them often. Check each official pricing page with your real volume. To find out first how much automating that process would save you, try the [automation ROI calculator](/en/tools/automation-roi-calculator). ## Which is better for self-hosting and GDPR? This point decides many choices for European companies, and it matters for any business with strict data rules. With **self-hosted n8n**, your customers' data passes only through the server you choose. You can run it with a European provider, on your own infrastructure or even on an internal network with no outside access. For accounting firms, law firms or clinics, which handle data covered by professional secrecy or health data, this simplifies GDPR compliance a lot. With **Make**, data passes through Make's cloud. Make offers EU hosting and the standard data protection documents, so you can use it under the GDPR without trouble. What you cannot do is take it out of its infrastructure. The practical question: does any client, contract or regulation require that data stay in a specific place? If yes, n8n. ## How do n8n and Make handle AI and agents? Both tools connect to OpenAI, Anthropic, Google and other model providers. The difference lies in how much control you have over the agent. ### AI in n8n n8n has AI nodes built on LangChain: - **Agent node**: a language model that decides which tools to use to complete a task. - **Memory**: so the agent remembers the conversation. - **Tools**: any other workflow or node can become an agent tool (check the calendar, search the CRM, create an order). - **Vector databases**: so the agent answers from your company documents (known as RAG). This lets you build a full [AI agent](/en/glossary/ai-agent) inside one workflow, with fine control over each step. ### AI in Make Make has modules to call the main models and has added agent features. For cases like "summarize this email" or "classify this ticket" it works well and is quick to set up. For agents with several tools, memory and hand-off logic to a person, n8n leaves more room. ## Which one is easier to learn? Make wins here. Its editor is very visual, modules are configured with clear forms, and someone without a technical background can build a first scenario in an afternoon. n8n asks you to understand better how data moves between nodes (JSON structures, expressions, multiple items). In return, when a flow gets complicated, n8n stays readable and lets you write code where visual logic runs out. A simple way to see it: - If the person who will maintain the flows is in operations with no technical training, Make. - If you have a technical person in-house or a provider who maintains it, n8n. ## What about maintenance and reliability? An automation that fails silently is worse than none: the team stops doing the task by hand and nobody notices it is no longer getting done. ### Maintenance in Make Make handles the infrastructure. You do not update anything or watch a server. Each scenario keeps an execution history, and you can add error routes per module and get email alerts when something fails. For a team without a technical profile, this is a clear advantage. ### Maintenance in n8n On n8n Cloud, as with Make, the vendor manages the infrastructure. If you self-host, someone has to: - Update n8n when new versions ship, which is often. - Back up the workflows and credentials. - Watch the server (memory, disk, uptime). - Protect access to the editor. In return, n8n lets you build a global error workflow that catches any failure and sends it to Slack, email or a monitoring tool, with the exact data of the execution that failed. On paid editions, it also lets you store workflows in Git and keep separate test and production environments. In practice, if you choose self-hosted n8n, count maintenance as part of the cost. If nobody can do it, n8n Cloud or Make are safer options. ## How do the integrations compare? Make has more native integrations. If you use niche applications, they are more likely to have a ready module in Make. n8n has fewer built-in nodes, but its HTTP Request node connects to any application with an API, and the community publishes additional nodes. In practice, almost all the tools a typical small business uses (Gmail, Outlook, Google Sheets, HubSpot, Pipedrive, QuickBooks, Xero, Shopify, WooCommerce, WhatsApp Business API, Slack) work in both. Before you decide, list your applications and check on each platform whether they have a connector and what operations it allows. ## When should you choose n8n and when Make? ### Choose Make if - Your flows are short (under 10 steps) and volume is moderate. - Nobody on your team wants to take care of a server. - You need native connectors for uncommon applications. - You want someone on the business side to build and adjust automations without help. ### Choose n8n if - You have long flows, with loops or thousands of runs a month. - You handle sensitive data and need to decide where it is hosted. - You want to build AI agents with tools, memory and your own documents. - You have a technical person or a provider to maintain it. ### What if you already use Make? You do not have to migrate everything. Check which scenarios use the most operations: usually two or three. Migrating only those to n8n can cut the bill without touching the rest. It is the same phased approach we apply to any project: first what saves the most, measured, then the rest. ## What do we recommend? At Gradual we work mostly with n8n, because most of our projects combine automation and AI, and because many clients need to control where their data lives. But we have seen companies for which Make works perfectly, and there is no point in changing something that works. If you want us to review your processes and tell you which tool fits, see our [n8n automation](/en/services/n8n-automation) service or [book your free first call](/en/contact), 30 minutes. ## FAQ ### Which is cheaper, n8n or Make? It depends on the workflow. With short flows and low volume, Make is usually cheap. With flows of many steps or thousands of runs a month, n8n usually costs less because it charges per complete execution, and you can self-host it with no license fee. ### Can you migrate from Make to n8n? Yes, but there is no reliable automatic import: you rebuild the flows in n8n. The usual approach is to migrate first the flows that use the most operations in Make, since they save the most, and leave the simple ones for last. ### Can you install Make on your own server? No. Make only runs as a cloud service. You can choose the hosting region for your account, but you cannot install it on your own infrastructure. If you need self-hosting, n8n is the option of the two. ### Which is better for building AI agents? Both can call AI models and build agents. n8n has agent nodes with memory, tools and vector database connections inside the workflow itself, which gives more control for complex agents. Make is simpler for basic cases.