Make vs n8n: Complete Comparison for Workflow Automation in 2025

Make and n8n take different approaches to workflow automation. Make offers a visual interface with 3,000+ pre-built modules, so you can get started with minimal setup. n8n offers open-source flexibility with self-hosting options and deeper customization, so you'll have more control over your infrastructure. This comparison breaks down interface usability, hosting, integrations, flexibility, pricing, and support from an operational perspective. Plus, it explains how Logic can become the intelligence layer, handling complex decisions while either platform moves the data.

Side-by-Side Feature Comparison

Here's how Make and n8n stack up on the six factors that matter most:

Both platforms require technical expertise to manage at scale. Make's visual interface feels more approachable at first, but complex workflows will still need dedicated automation specialists. n8n's flexibility comes with even steeper technical requirements, so you'll want technical resources on hand from the start.

Ease of Use and Getting Started

Make focuses on a visual canvas where you connect modules from a library of 3,000+ pre-built options and templates. Guided prompts walk you through OAuth connections, and when something breaks, it shows you which module stalled.

n8n uses a visual builder too, but exposes more technical controls: open any node and JSON fields appear alongside optional JavaScript inputs. Working with API keys, data pinning, and function nodes requires technical knowledge, so most teams need dedicated automation specialists to build and maintain these workflows effectively.

If your priority is avoiding code rather than working directly with APIs, Make may be a better option. n8n provides more customization options for teams with technical resources. Both platforms still require understanding workflow concepts like triggers, data mapping, and error handling.

Deployment Models and Hosting Control

When choosing an automation platform, where it lives matters as much as what it does. Make runs only in its managed cloud, so there are no servers, patches, or security updates. The trade-off is control. When your legal team insists that customer data never leaves a private network, Make's only workaround is an on-premise agent available on its Enterprise plan.

n8n approaches hosting as a spectrum. You can stay lightweight with its cloud service, or you can self-host the open-source edition for maximum data sovereignty. The flip side is responsibility. Someone has to provision the server, manage backups, and keep the instance patched.

Integration Breadth and Connectivity Options

Make's library includes 3,000 pre-built modules for tools like Google Workspace and Shopify, plus hundreds of niche SaaS platforms. Multi-step workflows like “Shopify sale to Airtable record to notification” use a modular approach, though configuring data flow between steps requires workflow expertise.

n8n starts smaller with roughly 1,000 integrations when you count community contributions, but it trades catalog size for total freedom. Any service with an API can connect through the HTTP Request node, and if you need a connector that doesn't exist, you can build your own. The tradeoff is handling manual API keys and basic JSON setup.

Workflow Flexibility and Customization Depth

With n8n, you draw the branches you need and keep building. Drop custom JavaScript into a Code Node to calculate shipping costs, reshape data, or call your internal systems without leaving the canvas. Advanced error handling keeps everything running, so you can pin sample data to test each step, set automatic retries, or trigger backup workflows when APIs fail.

Make shows workflow logic in a linear timeline: routers, filters, and built-in functions handle most business logic. The trade-off hits when complexity grows. Heavy data transformations can burn through operations fast, and real scripting requires Enterprise plans.

Pricing Models and Cost Predictability

Make charges by operation. Every single module that runs costs you. Whereas n8n bills by execution, so you'll get one charge for the entire workflow, no matter how many steps fire inside it.

Make starts free with 1,000 operations per month. The Core tier costs $9-10.59 monthly for 10,000 operations. Each step, loop, or error handler burns another operation, so a six-step campaign running 2,000 times monthly equals 12,000 operations.

n8n flips this completely. Self-host for free, server costs aside, or choose Starter Cloud at $20 for 2,500 executions. Pro Cloud runs $50 for 10,000 executions. Complexity stays "free," so you can add error handling, detailed logging, and AI enrichment without watching the meter tick.

Real numbers tell the story. You capture 1,500 leads monthly, enrich each through a data vendor, create CRM contacts, send notifications, log to spreadsheets. Six steps total.

• Make: 1,500 runs times 6 steps equals 9,000 operations, nearly your entire Core quota

• n8n: 1,500 executions use 60 percent of your Starter plan allowance

Choose Make if your workflows will stay simple and volume stays predictable. Choose n8n when complexity grows or volume spikes without warning.

How Logic Adds Intelligence to Make and n8n

Tools like n8n and Make are workflow orchestrators that reliably move data between platforms, handling complex decisions through elaborate if-then trees. Building order approval workflows or content review processes means creating dozens of conditional branches that grow brittle with each policy change. 

Logic works differently. It's a platform that transforms plain English instructions into intelligent decision-making APIs. Instead of visual logic trees, you write instructions like "Review this order against our fraud policies. Check for mismatched billing and shipping addresses, unusual purchase patterns, and high-risk product combinations. Flag orders that show multiple red flags for manual review." Logic figures out the branching logic, makes the judgment calls, and returns a simple decision. 

If n8n and Make move your data, where Logic excels is making complex decisions about that data, such as evaluating content against evolving policies, analyzing documents for compliance, or routing requests based on nuanced business rules. When you connect them through Logic's API, your n8n workflow calls Logic for decisions, receives structured responses, and continues orchestrating based on those results. n8n handles the "where does data go" question. Logic handles the "what should we do with it" question.

The initial API integration requires engineering work to set up, but once that's done, policy changes happen instantly.

Choosing the Right Workflow Platform

Make offers more integrations and community resources, while n8n offers better deployment, flexibility, and pricing. The choice comes down to your priorities and technical comfort level.

If you want a platform that is more visual and doesn't require coding, choose Make. It provides 3,000+ modules and comprehensive community resources, and the templates can accelerate your initial workflow creation.

Pick n8n when data sovereignty, self-hosting, or complex branching logic matter more than a visual approach. Because n8n charges per workflow execution rather than per individual step, costs will stay predictable even as you stack dozens of actions inside each run. Just know you'll need technical resources to manage it at scale.

Still torn? Spin up a quick proof-of-concept in both. You'll feel Make's speed and n8n's depth almost immediately.

Both platforms handle system connections and data routing, but they can struggle when workflows need to make complex judgment calls. That's where combining your workflow automation with an intelligence layer makes sense. While Make or n8n handles the data routing, a tool like Logic can handle the nuanced decision-making in plain English, so your business teams can update policies and rules without rebuilding entire workflows.

Ready to add intelligent decision-making to your workflows? Sign up for Logic and start automating complex judgments in plain English.