Deciding on the right workflow automation platform is a pretty big deal, whether you’re a seasoned pro looking for scalability or just starting your journey into connecting apps and saving time. Two major players often come up in this conversation: n8n and Make (you might remember it as Integromat). Both let you build powerful connections between different tools and services without writing tons of code, but they approach things differently and cater to slightly different needs. Understanding these nuances is key to picking the platform that won’t just get the job done today but will also support your growth and specific requirements down the road. Let’s dive in and see how they stack up.
Understanding the Core Philosophies
At their heart, both n8n and Make are visual workflow builders. You drag and drop pieces (nodes or modules) and connect them to create automated processes. But their underlying philosophies set them apart.
n8n’s Approach: Open, Flexible, Developer-Friendly
n8n brands itself as a powerful, source-available, and notably, self-hostable automation tool. What does “source-available” mean? It means you can actually see the code behind the platform, and “self-hostable” means you have the option to run it on your own server instead of just relying on their cloud service. This immediately tells you something important: n8n leans more towards users who appreciate control, transparency, and the ability to dig deeper if needed.
Think of n8n like a really versatile set of building blocks where you can even make new types of blocks if you’re a bit handy. Its visual editor uses “nodes” connected on a “canvas” to form “workflows.” It’s designed with a developer’s mindset often in mind, including features like a built-in JavaScript editor right in the workflow for complex data manipulation.
Make’s Approach: Polished, Accessible, Cloud-First
Make (formerly Integromat) has been around a bit longer and has refined its platform with a strong focus on user-friendliness and accessibility for everyone, regardless of technical background. It’s purely a cloud-based Software-as-a-Service (SaaS) offering. You don’t worry about servers or code unless you really want to (and even then, it’s often through their specific tools).
Make feels a bit more like a slick, ready-to-use toy set. Its building blocks are called “modules” and you connect them to form “scenarios.” The interface is often described as very intuitive, with colorful modules and a clear flow. Authentication (connecting your apps) is typically very smooth, with lots of native connections requiring just a few clicks to sign in. Make aims to abstract away complexity, making it easy to get started quickly.
Key Feature Comparison: A Head-to-Head
Let’s get down to the nitty-gritty differences in features that actually impact how you build and manage your automations.
User Interface & Experience (UI/UX)
Both platforms use visual editors, but they feel different. Make’s UI is often perceived as more polished and immediately intuitive for beginners. Its drag-and-drop is smooth, and the visual flow of “bundles” (data sets) through “scenarios” with “filters” and “routers” (for branching) is very clear.
n8n’s UI is functional and clear, using “nodes” and “workflows,” but it might feel a bit less “fancy” initially. However, for those with a bit of development background, the flow diagram feels natural. The ability to drop in a “Code” node and write JavaScript directly within the workflow is a huge plus for flexibility that Make doesn’t offer in the same way (Make has expression language and functions, but it’s not general-purpose code).
Connectivity & Customization
Both platforms boast a large and growing library of pre-built connectors for popular apps. Make might currently have a slightly larger number of direct integrations due to its longer history.
However, when it comes to custom integrations or connecting to less common services, n8n has a significant edge, especially for technically inclined users. Because it’s open-source and developer-friendly, you can build your own nodes or use the powerful HTTP Request node to connect to virtually any service that has an API, often without needing approval or going through a complex process. With Make, creating entirely new modules typically requires their development resources, which can mean waiting.
Handling Data & Logic
This is where things can get quite different. n8n treats data flowing between nodes in a flexible way, and its data structure handling, particularly with arrays and JSON, feels very natural if you’re comfortable with JavaScript concepts. Its “Merge,” “Split in Batches,” and “Set” nodes offer powerful ways to manipulate data within the no-code interface. Error handling is also baked in, allowing you to build specific error workflows.
Make uses an expression language for manipulating data within modules, which is powerful but requires learning Make’s specific syntax. Branching logic is handled elegantly with “Routers” and “Filters.” While Make has good debugging tools, setting up comprehensive error handling across complex scenarios can sometimes feel more cumbersome than n8n’s dedicated error workflows.
AI Capabilities
As automation evolves, so do the platforms. n8n has recently put a strong focus on integrating AI agents, allowing you to build workflows where AI models can dynamically decide which tools (nodes) to use to fulfill requests. This is a cutting-edge area and positions n8n well for future AI-driven automation.
The All-Important Cost Factor
Let’s be honest, pricing is a major consideration. This is one of the biggest differentiators between n8n and Make.
Make operates on an operations-based pricing model. What’s an “operation”? Essentially, every time a module in your scenario performs an action (like reading one record, sending one email, writing one row), it counts as one operation. A single scenario run can easily consume dozens, hundreds, or even thousands of operations if you’re processing multiple items or performing many steps. Costs can add up very quickly as your workflows become more complex or handle larger volumes of data.
n8n uses a different model: workflow executions. In their cloud offering, you’re charged per workflow run. It doesn’t matter how many nodes or how much data that single run processes; it counts as just one execution. This model is often significantly more cost-effective for complex workflows or those handling large datasets, as you’re not penalized for having many steps or processing many items within a single trigger.
Here’s a simplified look:
Feature | n8n | Make (formerly Integromat) |
---|---|---|
Hosting | Cloud or Self-hosted | Cloud only (SaaS) |
Pricing | Per Workflow Execution (Cloud) / Server Cost (Self-hosted) | Per Operation |
Code/Scripting | Built-in JS Code Node, Expressions | Expression Language, Functions |
Custom Integrations | Develop your own, HTTP Node flexibility | Request via Make, HTTP Module |
UI Vibe | Functional, Flow-diagram like | Polished, Block/Flowchart like |
Error Handling | Dedicated Error Workflows, Node-based | Step-by-step, Debugger |
Source Code | Source Available | Closed Source |
AI Focus | Strong focus on AI Agents | General automation platform |
Learning Curve | Can be steeper if non-developer | More accessible for beginners |
Now, the self-hosted option for n8n is where the cost advantage can become truly massive. You install n8n on your own server (which can cost as little as $5-$10 per month, depending on your provider and needs), and then you have un limited workflow executions (limited only by your server’s capacity, of course). This is a game-changer for cost-sensitive users or those with very high volume needs. Make, being purely cloud-based, doesn’t offer this possibility.
Real-World Considerations & Use Cases
Let’s think about that email categorization example from the source content. Say you get 2,500 emails a month, and your workflow involves triggering on a new email, sending it to an AI service for categorization, and then updating a spreadsheet with the results.
In Make, this might involve 3-5 modules per email. Processing 2,500 emails means 2,500 * (3-5) operations, potentially 7,500 to 12,500 operations. This might push you into a higher pricing tier relatively quickly.
In n8n (Cloud), this same process for 2,500 emails would be 2,500 workflow executions. This falls comfortably within their lower tiers (like a 2,500 execution starter plan).
If you self-hosted n8n, your cost would just be the server cost, potentially $5-$10, regardless of whether you processed 2,500 or 10,000 emails (within reason for server capacity). That’s a huge difference!
Self-Hosting: Power or Pain? Choosing the self-hosted route with n8n gives you immense control over your data and costs, which is fantastic for security compliance or scaling affordability. But, and this is a big but, it requires technical knowledge to set up and maintain the server. If you’re not comfortable with things like Docker, server management, and database backups, the cloud options (either n8n Cloud or Make) are probably better fits.
Community & Support: Both platforms have communities, but the n8n community is particularly active and helpful, partly because of its open-source nature. You often get support directly from engineers and experienced users in the forums. Make also has a community and paid support options, but the source content suggests community responses might not always be as consistent.
So, Which One Should YOU Choose?
Alright, the million-dollar question. Which platform wins? Honestly, it’s not about one being definitively “better” overall. It’s about which one is better for you right now.
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Choose Make if:
- You are brand new to automation and want the easiest possible entry point.
- You prioritize a polished, intuitive user interface.
- Your workflows are relatively simple or low-volume.
- You don’t want to deal with any server setup or maintenance.
- The majority of your integrations are covered by their extensive pre-built module library.
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Choose n8n if:
- You have some technical comfort (or are willing to learn).
- You need the ability to self-host for cost, control, or security/compliance.
- Your workflows are complex, high-volume, or require advanced data manipulation (like using custom code).
- You need to connect to less common services or build highly customized integrations.
- You value the flexibility of an open-source-like platform and a strong community.
- You’re keen on exploring cutting-edge features like AI agents.
- Cost-per-operation could become prohibitive for your use cases.
My personal take? If I were just starting out with zero automation experience, I’d probably try Make first. Its ease of use lets you grasp the core concepts of triggers, actions, and data flow without getting bogged down in technical details. But as soon as my needs grew, my workflows got complex, or I needed more cost predictability, I’d absolutely look at n8n, especially the self-hosted option. Learning the slightly different interface and concepts would be a natural progression, leveraging the automation skills I’d already built.
Ultimately, both are powerful tools. The best way to know for sure is to give them a try. Most offer free trials or tiers!