Most comparisons of these three platforms count connectors. One supports 1,500 apps, another 2,000, a third integrates with everything Microsoft. The table gets built, the biggest number wins, and the decision gets made on a metric that will not matter in six months.
Connector count is close to irrelevant for a specific business. You will use eleven integrations, not two thousand, and all three platforms almost certainly support the eleven you need. What will matter is whether the platform fits the environment it has to live in - where your data is allowed to sit, who will maintain the workflows when the person who built them is on leave, and what happens operationally when one breaks at an inconvenient time.
We build on all three. That is not a neutrality claim, it is context for the framework below: there is no version of this where we benefit from steering you to a particular platform.
Choose on environment, not features
Five questions decide it. Answer them in order, because the first two usually eliminate an option outright.
1. Where is your business already operating?
If your company runs on Microsoft 365 - Teams, SharePoint, Outlook, Dataverse, Azure AD for identity - Power Automate has an advantage no feature comparison captures. It inherits your identity model, your governance policies, and your compliance posture. Approvals surface in Teams. Permissions follow existing groups. Nothing new to administer.
Outside that ecosystem, much of that advantage disappears and you are comparing it on general merit, where it is competent but no longer obviously ahead.
2. Can your data live on someone else's infrastructure?
If you handle health data, financial records, or anything under a residency requirement, this question ends the discussion early. n8n is the only one of the three offering a genuinely self-hostable deployment where credentials are encrypted at rest on your own infrastructure and you control network access and audit logging.
Make is primarily cloud-based. Power Automate lives in Microsoft's cloud with the compliance posture that implies - excellent for most enterprises, unsuitable where data physically cannot leave your environment.
If your data has no such constraint, this question is neutral and you move on.
3. Who maintains these workflows in twelve months?
The honest answer changes the recommendation more than any feature.
Make is built for non-engineers. Visual, forgiving, quick to a working scenario. A marketing or ops person can build and modify without a developer. That is a real operational advantage, because workflows nobody can change become workflows nobody trusts.
n8n assumes comfort with APIs, expressions, and webhooks. The node-based interface and manual OAuth setup carry a steeper learning curve. In exchange you get custom code, real branching, and control that visual-first tools cannot match. A team with an engineer ships more here. A team without one gets stuck.
Power Automate sits between, with a fairly gentle path for standard Microsoft work and increasing complexity as you move toward Dataverse and custom connectors.
4. Are you building AI workflows or just calling AI APIs?
These are different requirements and the distinction matters.
Calling an AI API - send text, get a classification back - is well supported everywhere. Make's pre-built AI integrations make this particularly accessible to non-technical teams.
Building an agent that reasons, selects tools dynamically, and acts on results is architecturally different, and n8n is the strongest of the three here. Self-hosting also means models can run locally, which matters when the data being reasoned over cannot go to a third-party API.
Power Automate connects cleanly to Azure AI services, which is the right answer if you are already committed to that stack.
If you are unsure whether you actually need agentic behaviour or a deterministic workflow would do, settle that before choosing a platform - we cover it in AI agent vs workflow automation.
5. How does the pricing model behave as you grow?
The models differ structurally, and the difference compounds.
Make charges by operations - each module execution consumes one. A twelve-step scenario consumes roughly twelve operations per run, so cost scales with workflow complexity as well as run count. Published entry pricing starts around $9/month for 10,000 operations. Estimate operations-per-run before committing; this is the most common budgeting surprise.
n8n bills per execution regardless of how many nodes that execution touches, with cloud plans from roughly $20/month and a free self-hosted Community Edition where infrastructure runs a few dollars monthly. Complex workflows do not cost more to run, which suits deep multi-step automation.
Power Automate licenses per user or per flow, which is predictable and usually favourable inside a Microsoft estate where licences may already exist.
All figures above are published vendor pricing as of 2026; verify current rates before budgeting, since all three revise regularly.
Where each genuinely fits
Power Automate — the business already runs on Microsoft, workflows are internal, and governance and identity are already solved by existing IT policy. Choose it for the inheritance, not the features.
Make — SaaS-to-SaaS orchestration, non-engineering maintainers, speed to working automation valued above deep customisation. Choose it when the person who will change the workflow is not a developer.
n8n — custom logic, self-hosting or data-residency requirements, agentic workflows, or high volume where per-execution billing beats per-operation. Choose it when you have technical ownership and need control.
The mistake that costs the most
Choosing on capability and ignoring maintainership.
The most expensive automation failure we see is not a platform limitation. It is a technically excellent set of workflows built by someone who left, on a platform nobody remaining can debug. The workflows keep running until an API changes, then break, and the business discovers it has no path to fix them.
Platform capability is worth little if the workflow cannot be modified when the process changes - and processes always change. Weight question three heavily.
Deciding in an afternoon
List your eleven actual integrations, not the theoretical universe. Confirm all three support them; usually all three do, which removes connector count from the decision permanently.
Then answer the five questions in order. Microsoft-native and internal? Power Automate, decided. Data cannot leave your infrastructure? n8n, decided. Neither constraint applies, and the maintainer is non-technical? Make. Neither applies and you have engineering ownership with agentic ambitions? n8n.
Most businesses reach an answer before question five.
If you would rather have the environment assessment done against your actual stack, integration list, and team capability - and an honest read on where the maintainership risk sits - book an automation architecture review. We implement on all three, so the recommendation reflects fit rather than what we happen to resell.
