n8n vs Make (Integromat): Which Automation Platform to Choose in 2026

n8n and Make (formerly Integromat) are the two automation platforms businesses talk about most today when they want to stop copying data by hand between CRMs, e-commerce stores, spreadsheets and marketing tools. n8n is an open-source, self-hostable platform built for teams that want full control over code, data and infrastructure, with the option to install it on a company server or on a European cloud of your choosing. Make is a cloud-native platform, launched as Integromat in 2012 and rebranded in 2022, designed to build visual automations entirely from the browser with no server to manage. Choosing between the two means balancing available budget, the technical skills your company has in-house and your data-residency requirements: this guide compares pricing, self-hosting, learning curve, AI features, error handling and scalability to help you work out which automation platform actually makes sense for your business in 2026.

n8n and Make (Integromat): What Are They and How Do They Differ?

n8n is an open-source, fair-code workflow automation platform you can install on your own servers or use as n8n's managed cloud service, with a visual node-based editor and the option to write JavaScript or Python code directly inside a workflow when the standard nodes aren't enough. Make, launched in 2012 as Integromat and rebranded Make in 2022 after being acquired by Celonis, is a cloud-native automation platform with a visual scenario editor, where modules connected by arrows represent how data flows from one app to the next, designed to be used entirely from the browser with nothing to install. The core difference isn't really in the basic feature set - both connect hundreds of apps, handle conditional logic and transform data in real time - it's in the deployment model: n8n lets you choose where your workflow's code actually runs, Make always runs it on its own servers.

What's the Price Difference Between n8n and Make?

The key difference is that n8n bills by workflow execution (or costs nothing at all if you self-host it), while Make bills by the number of operations consumed inside your scenarios, regardless of who hosts the underlying infrastructure. n8n's cloud plan starts at around €24/month for a fixed number of active executions and scales up from there; if you install n8n on a VPS costing a few euros a month, or on a server your company already runs, the software itself is free and you only pay for infrastructure, with no cap on monthly executions. Make is cloud-only: the free plan includes 1,000 operations per month, the Core plan starts at around €9/month for 10,000 operations and climbs quickly as volume grows, because every single module executed in a scenario - even just a filter, a data transformation or a condition - consumes one operation from the total available. In scenarios with many steps, operation counts can outrun expectations within the first few months of use.

Which Platform Gives You More Data Control and EU Data Residency: n8n or Make?

For data residency and GDPR compliance, n8n has a structural advantage Make can't replicate: you can install n8n entirely on-premise, on a European cloud of your choosing, or even on air-gapped infrastructure, so no company data ever leaves your infrastructure or EU territory while workflows run. Make is cloud-only: even if you pick a European data center for your account, workflow data, credentials for connected apps and execution logs still sit on servers Make controls, outside the customer company's direct oversight. For a business handling healthcare or financial data, or one that simply wants to be able to show an auditor exactly where its data physically lives and who can access it, this difference often outweighs price in the final decision, especially in regulated sectors like healthcare, finance and the public sector.

Which Platform Is Easier to Learn: n8n or Make?

Make has a gentler learning curve in the first few weeks: the scenario editor, with modules linked by colored arrows, is designed to feel intuitive even for someone who has never written a line of code, and its large template library speeds up building your first automations in a matter of hours. n8n takes longer to master - its node canvas feels more like a visual development environment, with expressions for manipulating data, environment variables and the option to drop custom code into a single node - but that steeper initial curve pays off once you need intricate conditional logic, loops, nested-array handling or non-standard data transformations, situations where Make often forces you to work around interface limits with messier module chains. For a team that will only ever build simple automations, this barely matters; for one that expects complex logic down the line, n8n's steeper curve pays for itself quickly.

How Do n8n and Make Handle AI Agents and LLMs?

Both platforms have added native LLM and AI agent nodes in the last couple of years, but with different philosophies: n8n builds a genuine AI agent framework right into the workflow, with nodes for conversational memory, tool calling into other nodes in the same workflow (which effectively become 'tools' the agent can invoke) and native support for multiple providers - OpenAI, Anthropic, Google, plus self-hosted models via Ollama for anyone who doesn't want to send data to an external API - letting you build agents that decide on their own which tool to call based on context. Make offers AI modules and a more guided agent builder, aimed at anyone who wants to quickly drop a text-generation, classification or data-extraction step into an existing scenario, with less orchestration flexibility but much faster setup, often in just a few clicks. If you want to build complex AI agents with custom decision logic over sensitive data your company manages internally, n8n gives you more room to work with; if you just want to bolt one AI step onto an already-automated process without writing code, Make stays the quicker route.

Which Platform Handles Errors, Retries and Enterprise Workloads Better?

For enterprise workloads, n8n offers more granular control over error handling: you can set up dedicated error-handling workflows that trigger automatically when an execution fails, configure retries with custom logic and backoff, run queued executions on dedicated workers and - if self-hosted - scale horizontally by adding instances based on real load, with full visibility into the logs and response time of every single execution and node. Make handles automatic retries and error notifications simply and reliably for scenarios of moderate complexity, but its scalability depends on the limits of its operations-based plans and on infrastructure the company doesn't control directly, which can create bottlenecks when volume spikes unexpectedly or during seasonal peaks. For mission-critical automations with tight SLAs and high volumes, many companies prefer n8n self-hosted precisely so they can size their infrastructure independently rather than being bound by the limits of a consumption-based plan.

What Are the Pros and Cons of n8n and Make?

n8n or Make: Which Is Right for an SMB with Limited Technical Resources?

For a small or mid-sized business with no dedicated IT staff, a limited budget and relatively simple integrations - a handful of connected apps, a modest number of automations per month - Make is often still the more pragmatic choice: you're up and running the same day with no server to manage, and the free or Core plan comfortably covers modest volumes at a predictable short-term cost. That changes once the company already has in-house technical skills or a partner managing infrastructure on its behalf, handles data that must stay within the EU for contractual or regulatory reasons, or expects rapid growth in the number of automations and the volume of data processed: in those cases, n8n self-hosted removes the risk of bill shock tied to operation counts and offers technical headroom Make simply isn't built to provide. Budget sensitivity alone isn't enough to decide - what matters most is the growth trajectory you expect over the next two to three years.

• Fixed, predictable monthly budget even as volume grows → n8n self-hosted
• No in-house technical skills, need to launch immediately → Make
• Sensitive data with EU residency requirements → n8n self-hosted
• Simple automations, low volume, speed of setup matters most → Make
• Need for AI agents with complex decision logic → n8n
• Team with DevOps skills or an available technical partner → n8n

How Should You Choose Between n8n and Make in 2026?

The choice between n8n and Make in 2026 comes down to three questions worth asking before you even look at features: who inside the company will manage the automation over the next two years, where the data your platform touches needs to physically live, and how quickly the number of monthly operations will grow. If the answers point to limited in-house technical resources, low volumes and no data-residency constraints, Make offers the faster, lower-risk path. If instead the company has - or can bring in through a technical partner - the skills to manage infrastructure, handles sensitive data subject to regulatory constraints, or expects significant growth in the number of workflows and executions, n8n self-hosted pays back its initial setup effort with more predictable costs over time, tighter control over data and infrastructure, and a platform built to scale alongside the business without billing surprises.