If you're picking an automation platform and don't want to get locked into a per-operation cost that balloons over time, this comparison is for you. n8n, Activepieces and Make all solve the same problem —connecting apps and automating processes— but with different models: n8n is fair-code and self-hostable with fixed cost and the largest set of integrations; Activepieces is fully open source (MIT), simpler and cleaner; and Make is closed cloud that charges per operation. For SMBs that want independence and predictable pricing, n8n usually wins; Activepieces is best if you prioritize simplicity; Make only makes sense at low volume without a technical team. Let's dig in.
The difference that drives everything: licensing and how they charge
Before features, understand the three models, because that decides your two-year bill:
- Make is a closed SaaS. You can't install it on your own server: your data flows through their cloud and you pay per operation (each module that runs). Cheap to start, but cost scales with flow complexity.
- n8n is fair-code (Sustainable Use License). You can self-host it for free, modify the code and use it internally without paying. The only restriction: you can't resell it as a competing SaaS. It ships with 500+ integrations and the most advanced AI nodes.
- Activepieces is pure open source (MIT). No commercial-use restrictions, a growing community and an interface built to be approachable. Fewer integrations than n8n, but genuinely free code.
That conceptual difference is why so many companies that started on Make end up with bills that triple their budget: every flow improvement raises the per-unit cost.
Quick comparison: n8n vs Activepieces vs Make
| Criterion | n8n | Activepieces | Make |
|---|---|---|---|
| License | Fair-code (Sustainable Use) | Open source (MIT) | Proprietary (cloud) |
| Self-hosting | Yes, fixed cost | Yes, fixed cost | No |
| Native integrations | 500+ | 280+ ("pieces") | 1,800+ apps |
| AI / agent nodes | Advanced (LangChain, agents, memory) | Yes (AI blocks + copilot) | Basic (OpenAI modules) |
| Learning curve | Medium-high | Low-medium | Low |
| Complex logic | Excellent (JS/Python code) | Good | Limited (routers) |
| Cloud cost model | Per execution | Per task | Per operation |
| Best for | Scaling and complex logic | Simplicity + free license | Starting fast, low volume |
Not sure which one fits your operation and team? In a 30-minute call we'll tell you honestly which platform suits your case and what it would cost to implement. Book a presentation meeting and walk away with a clear plan.
Real pricing at three volume levels
Price is where the decision gets concrete. These are typical SMB scenarios:
- Small flows (up to ~10,000 ops/month): Make's Core plan (USD 10.59/month) or even the free tier is enough. Self-hosted n8n or Activepieces cost a USD 10-20/month VPS, but you add maintenance time. At this volume, Make wins on convenience.
- Medium volume (~50,000-100,000 ops/month): here Make starts to hurt. An 8-module scenario processing 100 records burns 800 operations; the plan you need climbs to USD 30-100/month. Self-hosted n8n and Activepieces stay on the same USD 10-20/month VPS. The scale already tips toward open source.
- High volume or many flows (200,000+ ops/month): Make gets genuinely expensive (USD 100-300+/month). An n8n or Activepieces on a USD 20-40/month VPS runs unlimited workflows. A difference of thousands of dollars a year.
Rule of thumb: below USD 30/month in billing, stay where you're comfortable. Above a sustained USD 50/month, self-hosted open source almost always wins. If you want that server set up and monitored properly from day one, that's exactly what we do under AI automation.
n8n: the most powerful for scaling
n8n is the king of flexibility. Its 500+ integrations cover almost everything, and when one is missing you can call any API with the HTTP node. What sets it apart is the AI layer: agent nodes, built-in LangChain, conversation memory and the ability to build AI chatbots or AI agent flows without leaving the tool.
The cost: the learning curve. You need to understand JSON, expressions and sometimes write a bit of JavaScript. For a non-technical user, the ramp is steeper. But in exchange it handles logic that becomes a maze of routers in Make.
Choose n8n if: you're going to scale, you need serious AI, you handle sensitive data you don't want in someone else's cloud, or your business logic is complex.
Activepieces: the cleanest and fully free
Activepieces is built for simplicity. Its interface is tidier than n8n's, the blocks (which they call "pieces") come well pre-configured, and it added an AI copilot to build flows by describing them in plain language. Its MIT license makes it the most "free" of the three: no commercial-use fine print.
The downside: fewer integrations (around 280 versus n8n's 500+) and less depth in advanced logic. For tangled flows with many branches and data transformations, you'll hit limits sooner than with n8n.
Choose Activepieces if: you value a clean interface, your team isn't technical, your flows are low-to-medium complexity and you care about a fully open license.
Make: comfortable to start, expensive to scale
Make (formerly Integromat) is still the easiest to start with and has the most raw integrations (1,800+ apps). Its circular visual editor is very intuitive and you don't need to touch anything technical for your first flows. The problem is structural: you can't self-host it and you pay per operation forever. As your scenarios get richer, the per-operation cost penalizes you for improving them.
Stay on Make if: your volume is low, you have nobody to run a server and you want zero maintenance.
When moving to open source does NOT make sense
Let's be honest, because migrating has a real cost:
- Your Make bill is under USD 30/month. The savings won't pay for migration time or maintenance. Stay put.
- You have nobody to administer a server. A self-hosted n8n or Activepieces needs updates, backups and monitoring. Without that, one day it goes down and nobody knows why.
- Your flows are 4 or 5 simple, stable scenarios. If they won't grow, Make's convenience is worth more than the savings.
- You need an exotic integration only Make has. With 1,800+ apps, Make sometimes ships connectors that in n8n mean building the API call by hand.
If you fall into any of these, don't migrate for the trend. Automation pays off when it removes a concrete bottleneck, not when you swap logos. When the case calls for something more tailored than any standard platform, it's worth evaluating custom software or exposing your processes via API development.
Verdict
For most SMBs that want predictable pricing and control: n8n is the safest bet thanks to its integrations, AI and ability to scale. Activepieces is the best pick if you prioritize simplicity and a fully free license. Make still makes sense only at low volume and without a technical team. The question isn't "which is best" but "which fits your volume, your team and your business logic."
Want to skip the trial and error and set up the right platform properly from the start? Start your project with us: we analyze your processes, pick the right tool and leave your automations running with fixed cost and no surprises.
Frequently asked questions
What is the best open source alternative to Make?+
For most SMBs, n8n is the best open source alternative to Make: 500+ integrations, native AI agent nodes and a self-hosted model with fixed cost. Activepieces is the strong runner-up, with a cleaner UI and a fully permissive MIT license, ideal if you value simplicity and don't need very complex logic.
Is n8n really open source?+
n8n uses a 'fair-code' license (Sustainable Use License), not a classic OSI one. You can self-host it for free, modify the code and use it internally without paying, but you can't resell it as a competing SaaS. Activepieces, by contrast, is pure MIT. Make is not open source at all: it exists only as a cloud product.
Activepieces or n8n for a non-technical team?+
Activepieces has the gentler curve: a cleaner interface, fewer technical concepts and a more no-code feel. n8n is more powerful but expects you to understand JSON and expressions. If nobody on your team codes and your flows are simple, start with Activepieces; if you plan to scale into complex logic, n8n pays off long term.
How much does it cost to self-host n8n or Activepieces?+
Both run on a USD 10-20/month VPS (2 GB of RAM is enough to start). That cost is fixed: you don't pay per operation or per task like Make. The real difference is in setup and maintenance time, not in hosting.
When should I stay on Make instead of moving to open source?+
Stay on Make if your volume is low (under ~10,000 operations a month), you have nobody to administer a server and you value zero maintenance. The free plan or the USD 10.59/month Core plan are plenty for small flows without headaches.
Does Activepieces have AI features like n8n?+
Yes. Activepieces added AI blocks and a copilot to build flows, plus connections to OpenAI and other models. n8n goes further with AI agent nodes, built-in LangChain and memory, so it remains the strongest choice for advanced AI automation.
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