Make vs n8n: Which Automation Tool Is Better for a One-Person Business?

Make and n8n solve the same basic problem — connecting apps and moving data between them without writing custom integration code for every pair of services — and on the surface, their feature lists overlap heavily. The decision that actually matters for a one-person business isn’t which tool has more integrations or a longer feature list. It’s which one you’ll still be running smoothly in six months, without automation maintenance quietly becoming a second job.

This comparison is built around that question rather than a feature-by-feature checklist.

Quick Verdict

Choose Make if you want to automate business workflows quickly without turning workflow infrastructure into a technical project of its own — visual setup, managed hosting, no server to maintain.

Choose n8n if you value self-hosting, custom code inside your workflows, or full control over where your data lives enough to accept more setup time and some ongoing maintenance.

Choose neither, for now, if you have a handful of repetitive tasks and the time to set up and maintain either tool exceeds the time either would actually save you.

The rest of this article explains why, section by section — pricing, hosting, AI capabilities, and the maintenance burden each one actually creates for someone running a business alone.

Ease of Use

Make is built entirely around a visual canvas: modules connected by lines, no code required anywhere in the default path. Scenarios (Make’s term for a workflow) are built by dragging modules onto a canvas and configuring each one’s fields — the learning curve is mostly “understand what each module does,” not “learn a scripting language.” Make’s official app catalog and pre-built templates mean a lot of common automations (form to spreadsheet, email to task manager) can be assembled from existing pieces without touching raw JSON or code at any point.

n8n is also visual — nodes on a canvas, connected by lines, conceptually similar to Make at first glance. The difference shows up the moment a workflow needs logic that doesn’t fit a pre-built node: n8n supports custom code inside workflows — primarily JavaScript, with Python available in a more constrained form (more on that distinction below). That’s a real capability, not a limitation dressed up as a feature — but it also means n8n’s ceiling for “how complicated can this get” is higher, and so is the floor of technical comfort needed to use that ceiling. A nontechnical operator can build simple n8n workflows using only pre-built nodes and never touch code. The moment a workflow needs custom logic Make can’t express visually, n8n’s code option becomes the difference between solving the problem and not.

For a nontechnical solo operator with a fairly standard workflow — form submission to CRM, inbox rule to task, file to folder — Make’s fully visual approach requires less learning to get to a working result. For an operator comfortable writing a few lines of JavaScript, n8n’s code option removes a ceiling Make’s visual-only model eventually hits.

Integrations

Make’s catalog of pre-built app integrations is substantially larger than n8n’s, but the two platforms don’t necessarily count integrations the same way, so a raw number-versus- number comparison isn’t a reliable signal on its own. For a solo operator, the useful question is whether the specific services you need are covered — and what happens when one isn’t.

Both tools support generic HTTP/API modules for connecting to any service with a REST API, which matters more than the headline integration count: neither tool is actually limited to its pre-built app list. Make’s HTTP module is visual-configuration only. n8n’s equivalent can be paired with a code node when an API’s response needs custom transformation before the next step can use it — the same distinction as the Ease of Use section: n8n’s code option becomes relevant exactly when a pre-built integration doesn’t fully cover what you need.

Practically: check whether the specific services you need to connect (your email platform, your CRM, your payment processor) are on each platform’s own integrations list before assuming either one “has more integrations that matter to you.”

AI and Agent Workflows

Both platforms have built out AI-agent-style capabilities in the current generation of their products, and both let you connect models like OpenAI, Claude, or Gemini into a workflow rather than locking you into one AI vendor.

Make’s AI Agents (currently in beta) are configured visually on the same canvas as the rest of a scenario — an agent can act on goals and unstructured input (files, conversation history) and make adaptive decisions rather than following a fixed step sequence, with step-by-step execution logs for visibility into what the agent actually did. Make also supports the Model Context Protocol (MCP) for connecting external AI tools and services.

n8n’s AI workflow tooling is built around the same node-based canvas as everything else, with explicit support for multi-agent setups and retrieval-augmented generation (RAG) pipelines, plus what n8n describes as human-in-the-loop approval steps for governing what an agent is allowed to do autonomously. Because n8n supports code nodes, an AI workflow can include custom preprocessing or postprocessing logic around a model call in a way that’s harder to express in Make’s visual-only modules.

For a one-person business, realistic AI-workflow use cases on either platform look similar: routing and summarizing inbound leads, drafting first-pass replies for human review, enriching CRM records from public data, or turning a long document into a structured summary. Neither platform’s AI capability is a reason to choose it on its own — the underlying question is still which platform’s overall model (visual-only vs. visual-plus-code) fits how you want to build and maintain the workflow the AI step lives inside.

Flexibility and Custom Code

Make is intentionally a no-code tool. There is no supported way to drop into a scripting language inside a scenario for custom logic — if a transformation isn’t covered by an existing module or Make’s built-in functions, you’re working around the limitation rather than solving it directly. For most day-to-day business automation (the kind covered in CraftSolo’s own Make.com guide) this ceiling rarely gets hit. It becomes a real constraint for workflows with genuinely custom business logic — unusual conditional rules, complex data restructuring, or anything that would be a few lines of code in a general-purpose language but has no clean visual equivalent.

n8n removes that ceiling by design, with code nodes that can sit anywhere in a workflow. JavaScript is the fuller-featured option here — n8n’s own documentation treats it as the primary language for the Code node. Python is genuinely supported, but with real constraints worth knowing before it factors into your decision: on n8n Cloud, the Python option can’t import external or standard-library packages at all, it supports a narrower set of n8n’s built-in workflow variables than JavaScript does, and it runs slower due to extra compilation steps. Self-hosting relaxes some of this, but if custom code is a significant part of why you’re choosing n8n, plan around JavaScript rather than assuming Python gives you the same reach.

This is real flexibility, not a marketing claim — but flexibility has a cost that’s easy to underweight when comparing tools on a feature list: a workflow that uses custom code is a workflow only someone who can read that code can debug six months later when it breaks. For a solo operator, “flexible enough that only I can maintain it” is a tradeoff worth naming explicitly, not an unambiguous win.

Cloud vs. Self-Hosting

This is the section most Make-vs-n8n comparisons oversimplify, because it changes the actual economics of both tools.

Make is cloud-only. There’s no self-hosted option — you use Make’s managed infrastructure, full stop. That’s a real product decision with a real benefit: no server to provision, patch, secure, or monitor. The tradeoff shows up later rather than immediately: your scenarios live on Make’s platform, and if credit economics stop fitting your workload or you eventually need infrastructure control Make doesn’t offer, moving elsewhere means rebuilding those workflows rather than simply running the same system yourself. That’s not a reason to avoid Make — it’s the dependency that comes attached to managed convenience.

n8n offers three paths: n8n Cloud (managed, similar in spirit to Make’s model), or self-hosting the open-source Community Edition on your own server. n8n Cloud has no permanently free tier — only time-limited trials — so “free n8n” specifically means the self-hosted Community Edition. Under n8n’s Sustainable Use License, the Community Edition is free to use for your own internal business purposes, with no execution limit imposed by the license itself and access to the full set of 400+ integrations; the paid tiers add features like SSO, advanced role-based permissions, environments, and Git-based version control, not core workflow capability.

That covers running n8n for your own business. It doesn’t automatically cover every client-service model. n8n’s own licensing guidance draws a line between consulting — building workflows for a client’s own n8n setup is generally fine — and hosting: running client workflows and client credentials inside an instance you operate is a different arrangement that n8n’s current guidance says needs a commercial license. If you’re building an automation agency rather than automating your own operations, that distinction is worth checking against n8n’s current license terms for your specific setup before you build a business model around it.

“Free to self-host” is not the same as “free.” Running n8n yourself means you’re now responsible for a server (a small VPS is enough for light use, but it’s a real recurring cost), a database for production use, security patches, uptime monitoring, and the time to set all of that up correctly and keep it running. None of that shows up as a subscription line item, which is exactly why it’s easy to undercount. The honest framing: self-hosting n8n trades a monthly software fee for a smaller, less visible, but nonzero ongoing time cost. Whether that trade is worth it depends entirely on whether you (or someone you’re paying) actually wants to own that infrastructure work.

Pricing Economics

Comparing “$X vs $Y” directly is misleading here because the two platforms bill on different units entirely. Make bills in credits: for most standard, non-AI modules, one operation (one module action in a scenario) consumes one credit, though some AI and advanced features use credits dynamically based on factors like token usage or processing load. n8n Cloud charges per workflow execution, regardless of how many steps that execution contains. A ten-step Make scenario that runs once consumes roughly ten Make credits; the equivalent ten-step n8n workflow running once consumes one n8n execution. That difference alone makes a naive price-per-dollar comparison meaningless without knowing your actual workflow shape.

Three rough scenarios, using each platform’s current published pricing (checked against official pricing pages, August 2026 — verify current figures before deciding, since pricing changes):

Light solo workflow (a handful of simple automations, low volume): Make’s free plan (1,000 credits/month, up to 2 active scenarios) or n8n’s free self-hosted Community Edition on a low-cost VPS both cover this comfortably. Make requires no setup beyond the workflow itself; n8n requires basic server setup. (n8n Cloud itself has no permanently free tier — only time-limited trials — so this “free” comparison is specifically Make’s free plan against self-hosted n8n, not n8n Cloud.)

Moderate multi-app automation (several scenarios/workflows, a few hundred to a couple thousand runs a month, each with multiple steps): Make’s Core plan ($9/month for 10,000 credits) can be consumed quickly if scenarios are step-heavy, since every module counts against the credit pool. n8n Cloud’s Starter plan (€20/month for 2,500 executions) counts whole workflow runs regardless of step count, which can go further for step-heavy workflows — or self-hosting remains free software-wise, at the cost of the maintenance time described above.

Technically sophisticated, high-volume workflow (many steps per run, high frequency, custom logic): Make’s credit model means cost scales directly with workflow complexity, which can get expensive fast for step-heavy scenarios at volume. n8n’s execution-based model is more forgiving of complex individual workflows, and self-hosting removes the per-execution cost ceiling entirely — at the cost of needing real infrastructure and monitoring at that volume, which stops being a casual weekend setup.

These are illustrative scenarios based on each platform’s published pricing structure, not guarantees about your specific costs — actual usage varies enormously by workflow design, and both platforms’ pricing pages should be checked directly before budgeting.

Maintenance and Reliability Burden

This matters most for a one-person business and gets the least attention in most comparisons, because it doesn’t show up in a feature table.

The real question isn’t “which tool can build this workflow” — both usually can. It’s:

Are you automating your business, or creating another system you now need to maintain?

Make’s managed-cloud model means Make’s team handles infrastructure uptime, security patches, and platform reliability. Your maintenance burden is limited to the workflows themselves — fixing a scenario when a connected app changes its API, adjusting filters when edge cases appear. That’s real ongoing work, but it’s bounded to the automation logic, not the platform it runs on.

n8n Cloud carries a similar profile to Make on this dimension — n8n’s team manages the infrastructure. Self-hosted n8n adds a second maintenance surface on top of the workflow maintenance every automation tool requires: server updates, n8n version upgrades, database maintenance, and being the person who gets paged (literally or figuratively) if the server goes down at 2 a.m. and an automation touching customer communication silently stops running.

Neither tool removes the need to design for failure — a scenario or workflow that fails silently on a customer-facing process is a bad outcome regardless of which platform built it. What changes between the two is how many layers of infrastructure exist between “it broke” and “someone finds out.”

Realistic One-Person Business Use Cases

Lead form → enrichment → CRM → notification. Both platforms handle this well with pre-built integrations. Make’s visual setup is typically faster to get working end-to-end for a standard version of this workflow; n8n’s code option matters if enrichment requires custom API logic a pre-built module doesn’t cover.

Newsletter research and admin workflow (pulling source material, formatting for review, scheduling). Straightforward on either platform — this is exactly the kind of structured, repeatable workflow neither tool’s advanced features are really needed for.

Ecommerce order and admin processing (order to fulfillment notification, inventory sync, customer service ticket routing). Make’s broader pre-built ecommerce-platform integrations can mean less setup for standard platforms; a workflow requiring custom business logic around order routing is where n8n’s code nodes become the more direct path.

AI research and content pipeline (source gathering, summarization, draft generation, repurposing into formats). Both platforms’ current AI-agent tooling covers this reasonably well; the choice mostly comes down to whether the surrounding workflow needs Make’s simplicity or n8n’s custom-logic ceiling more than the AI step itself does.

Client onboarding and reporting (intake form to task creation to scheduled report generation). A good fit for either platform’s standard visual capabilities — this is the category of workflow where the choice between Make and n8n usually comes down to hosting preference and pricing model rather than a capability gap.

When Make Is Better

• You want to be building working automations within the first sitting, with no code and no server to think about.
• Your workflows fit comfortably within what visual modules and built-in functions can express — most day-to-day business admin automation does.
• You’d rather pay a predictable subscription than take on any infrastructure responsibility, even a small one.
• Your automation volume is moderate enough that credit-based pricing doesn’t become expensive relative to the value each scenario delivers.

When n8n Is Better

• You want custom logic that Make’s visual modules genuinely can’t express, and you’re comfortable writing (or learning to write) the JavaScript to do it.
• Self-hosting matters to you — for cost at scale, for data residency, or because you simply want your automation infrastructure under your own control.
• Your workflow volume is high enough that execution-based pricing (or free self-hosting) meaningfully beats Make’s credit model.
• You’re willing to own basic server maintenance in exchange for removing Make’s visual-only ceiling and per-credit cost scaling.

If n8n’s self-hosting model or code flexibility fits your situation better, n8n’s own site is the place to start — its Community Edition documentation and pricing page cover current self-hosted and cloud options in full.

When Neither Is Better

If you have two or three genuinely repetitive tasks and each one takes a few minutes a week, the setup time for either platform — learning the interface, building and testing the workflow, handling edge cases — can easily exceed a year’s worth of time saved. This isn’t a hypothetical: it’s the most common reason a well-intentioned automation project becomes its own maintenance burden without ever paying back the time it cost to build. If a task happens rarely, or the process it’s part of is still changing shape, the honest answer is often to keep doing it manually a while longer and revisit automation once the workflow has stabilized.

Final Decision Framework

Pick Make if you want the fastest path from “I have a repetitive task” to “it’s automated,” you’re not planning to write custom code, and a predictable monthly fee beats any amount of infrastructure ownership — even a small amount.

Pick n8n if you’ve hit (or expect to hit) a wall Make’s visual-only model can’t solve, self-hosting or data control matters to you specifically, or your workflow volume makes execution-based pricing (or free self-hosting) a meaningfully better economic fit than Make’s credit model.

Stay manual for now if the tasks you’re considering automating are infrequent enough, or still changing shape enough, that the setup time for either tool wouldn’t pay itself back within a reasonable window. Revisit once the workflow is stable and genuinely repetitive.

Where to Go Next

How to Automate Your Inbox and Admin With Make.com covers how to find genuine automation candidates and build them with Make specifically, in depth — the natural next read if Make is the fit from this comparison.

An AI Tool Stack for Running a One-Person Business covers where automation fits into a minimum overall tool stack, not just which specific platform to use.

One-Person AI Business Ideas That Actually Work in 2026 covers the AI automation service business model specifically, if you’re evaluating Make or n8n as the tool behind a service you’d sell to other small businesses rather than just for your own operations.