Make.com vs n8n is a choice between convenience and control. Make is a fully hosted visual platform that is quick to learn, has a large library of app modules and bills per module run in credits. n8n is a workflow tool that you can use on n8n Cloud or self-host, bills per workflow execution rather than per step, and gives you code, AI agent nodes and full control over your data. For most agencies with a non-developer team maintaining automations, Make is the faster start. For agencies with heavy volume, complex logic, AI agents or someone technical on staff, n8n often wins over time.
I build in both. All of the production builds I cite on this site run in Make, and I build n8n workflows when a client needs self-hosting or more complex AI work. This comparison tries to be fair to both.
Make vs n8n: the short version
- Pick Make if your team wants a visual tool they can maintain themselves, you mostly connect popular SaaS apps, and you do not want to manage servers.
- Pick n8n if you run high volumes or long multi-step workflows, want to self-host for cost or data control, need custom code, or are building AI agents with tools.
- Use both if you already have Make scenarios that work and want n8n for new, heavier workloads. There is no rule that says you need one tool.
Make vs n8n pricing
The pricing models are fundamentally different.
Make: credits per module
Make bills in credits. According to Make's pricing page, most actions use one credit, including searches, iterators and aggregators, while the Router and error handlers do not. A scenario with ten modules that runs 1,000 times uses roughly 10,000 credits, more if iterators multiply bundles. My Make.com pricing vs Zapier post explains how to estimate this.
n8n: executions per workflow
According to n8n's pricing page, n8n Cloud plans bill by workflow executions. One run of a workflow is one execution, whether it has three nodes or thirty. Plans also differ in concurrent executions, maximum execution duration and log retention, so check the plan details, not just the execution count.
n8n can also be self-hosted. The community edition is available on GitHub under n8n's sustainable use license, and you pay for the server and your time to maintain it. A paid self-hosted Business plan adds features for teams. See n8n self-hosted vs cloud for the full picture.
Which is cheaper?
For short workflows at modest volume, they are often close. For long workflows, loops over big lists or high volume, n8n's per-execution model usually costs less, and self-hosting can cost less again if you have the skills. For an agency without technical staff, the time cost of running n8n can outweigh the savings. Run your own numbers against both current pricing pages.
Ease of use
Make's canvas is approachable. You see bundles flowing between modules, you click to map fields, and the run history shows exactly what each module received and returned. Most account managers can learn to adjust a Make scenario.
n8n is also visual, but it assumes more comfort with data. You work with JSON items and expressions more directly, and the Code node is a common part of real workflows. It is very learnable, but it is a step up. In my experience, agencies where nobody is comfortable reading JSON struggle to maintain n8n on their own.
Power and flexibility
n8n has the edge for developers:
- Code anywhere. JavaScript or Python in Code nodes, and expressions in any field.
- AI agents. Native AI agent nodes that can use tools, memory and vector stores. See my n8n AI agent tutorial.
- Sub-workflows. Reusable workflows called from others, which helps with agency-wide logic.
- Self-hosting. Run it next to your own databases and internal services.
Make is strong too:
- Huge module library with well-built app integrations.
- Routers, iterators and aggregators that make data handling visual.
- HTTP and JSON modules for any API without a native app.
- Data stores for simple persistent state. See Make.com scenario variables and data stores.
Error handling
Both handle errors well when you set them up. Make attaches error handlers to individual modules: Retry (formerly Break), Skip (formerly Ignore), Resume, Commit and Rollback, plus incomplete executions you can retry. See Make.com error handling. n8n uses node-level settings like retry on fail and continue on error, plus a separate error workflow that runs when any workflow fails, which is a clean way to send all failures to one Slack channel.
Hosting, data and compliance
Make is cloud only. Your data passes through Make's infrastructure, and settings like keeping run data confidential control what is stored. n8n Cloud is similar, but self-hosted n8n keeps everything on your server. If a client has strict data requirements, self-hosted n8n is often the deciding factor. It also means you are responsible for security, backups and updates.
Make vs n8n for agencies: decision criteria
- Who maintains it? Non-developers lean Make. Developers lean n8n.
- How much volume? Long workflows at high volume favour n8n's per-execution pricing.
- AI agents? n8n's agent nodes are more flexible for tool-using agents.
- Data control? Strict requirements favour self-hosted n8n.
- App coverage? Check that the exact triggers and actions you need exist on both. Either can fall back to raw HTTP.
- Existing investment? If your Make scenarios work, migration has a cost. Move workloads only when there is a clear reason.
What I build in each
Make is my default for agency operations: onboarding, alerts and syncs between ClickUp, Slack, Google Workspace and CRMs. For example, the client health monitor alerts the right CSM when a ClickUp health field changes, routed by owner with context from Sheets, and the AI Client Wins Slack bot pulls context from Docs and posts formatted wins with separate live and test channels.
I reach for n8n when a client wants self-hosting, needs an AI agent that calls several tools, or runs workflows that would be expensive per step in Make.
A note on migration effort
If you already run a lot of Make scenarios, switching to n8n is not a weekend job. Each scenario has to be rebuilt as a workflow, every connection recreated as a credential, every webhook URL updated in the sending apps, and every flow retested with real data. My advice is to leave stable Make scenarios alone and use n8n for new work where it clearly fits, such as AI agents or high-volume jobs. Revisit the rest when a scenario needs a major change anyway, because that is when a rebuild costs the least extra.
How I build this
I help agencies pick the right tool for each job and build it with naming, error alerts and documentation. See my workflow automation service, my custom AI agents work, or check pricing for fixed-price builds. If you want a second opinion on your current setup, request a free 15-minute Loom teardown.
FAQ
Is n8n better than Make?
Neither is better overall. n8n is more flexible and can be self-hosted, while Make is easier for non-developers and fully managed. The right choice depends on who maintains it and how complex your workflows are.
Is n8n cheaper than Make?
Often for long or high-volume workflows, because n8n bills per execution rather than per step and can be self-hosted. For small workflows the difference can be minor, so compare current pricing pages.
Can I migrate from Make to n8n?
Yes, but there is no automatic converter you should rely on. Most migrations mean rebuilding each scenario as a workflow and testing it, so move the ones that benefit most first.
Is Make or n8n better for AI agents?
n8n has native AI agent nodes with tools and memory, which makes complex agents easier. Make can call AI models and build simpler AI steps well.