AI and automation
n8n, Make, or Zapier: which one fits?
Cost, data residency, flexibility, and the cases where a custom build beats all three. The comparison for European teams choosing an automation platform.
TL;DR
- Zapier is the fastest to start, easiest to use, and most expensive at scale. Best for small teams with simple, linear workflows.
- Make (formerly Integromat) is more flexible than Zapier and cheaper at volume. The learning curve is steeper but manageable for technical operations teams.
- n8n is open-source and self-hostable, which means full data residency control and no per-operation pricing. The trade-off is deployment and maintenance overhead.
- Custom builds make sense when the workflow has complex conditional logic, requires real-time data processing, or needs to integrate with systems the platforms do not support natively.
- Read more about how we deliver AI and automation workflows for European companies.
What each platform is built for
Three tools, three different answers to the <em>complexity vs. speed</em> trade-off.
Zapier was built for non-technical users who need to connect popular SaaS tools without code. The interface is intentionally simple, the app library is the broadest of the three (6,000+ integrations), and the first workflow can be running in under an hour. The cost model is per task, which becomes expensive quickly at volume: moving 10,000 tasks per month through Zapier costs €100 to €300 per month depending on the plan.
**Make (formerly Integromat) offers a visual workflow builder that handles branching logic and data transformation better than Zapier.** It is better suited for workflows with conditional paths, loops, or data manipulation between steps. Pricing is per operation, not per task, and the per-operation cost is lower. The interface is more complex, and building non-trivial workflows requires a technical operator.
n8n is open-source and can be self-hosted on your own infrastructure. Self-hosting removes per-task costs entirely and gives you full control over where data lives, which matters for GDPR compliance in regulated sectors. The cloud version (n8n.io) offers managed hosting. The trade-off is setup time: getting n8n running in production requires a server, maintenance, and someone who can debug when a workflow fails silently.
Side-by-side comparison
Cost, flexibility, and data control across the three platforms.
| Dimension | Zapier | Make | n8n (self-hosted) |
|---|---|---|---|
| Starting price | ~€29/month (Starter) | ~€16/month (Core) | Free (self-hosted) / ~€20/month (cloud) |
| Cost at 50k tasks/month | €250–€600/month | €60–€150/month | Hosting cost only (~€20–€80) |
| Native integrations | 6,000+ | 1,800+ | 400+ (extensible via code) |
| Branching / logic | Basic | Advanced | Advanced |
| Data residency control | Limited (US servers) | Limited (EU option available) | Full (self-hosted) |
| Technical skill required | Low | Medium | High |
| Setup time (first workflow) | Under 1 hour | 1–4 hours | 2–8 hours (incl. server setup) |
| Custom code support | Limited (Code step) | Yes (HTTP, code modules) | Full (JavaScript/Python nodes) |
| Best fit | Simple, high-volume Saas connections | Complex logic, data transformation | GDPR-critical, high volume, budget-sensitive |
When each fits
Match the tool to the workflow complexity, not the brand name.
01
Choose Zapier for simple, urgent connections between popular SaaS tools
A new lead in your CRM triggers a Slack notification. A form submission creates a task in Asana and sends a confirmation email. These are the workflows Zapier was built for. The integration library covers 99% of popular business tools. If the workflow is linear and the tools are common, Zapier gets you live fastest. Review the per-task cost at your expected volume before committing.
02
Choose Make for workflows with branching logic and data transformation
Incoming orders need to be routed to different fulfilment paths based on product type, customer segment, and regional rules. Make handles this kind of conditional logic cleanly. It is also significantly cheaper than Zapier at volume. The visual editor shows the full flow, which makes debugging easier than Zapier for complex multi-step sequences.
03
Choose n8n when data residency or cost at scale is the constraint
You are in a regulated sector (finance, health, legal) and your workflows touch personal data. Or your automation volume is high enough that per-task pricing has become a material cost. n8n self-hosted gives you full control over data location and eliminates per-task fees. The investment is deployment and ongoing server maintenance. For companies with a technical team already, the trade-off usually favours n8n above 100k tasks per month.
04
Build custom when the workflow does not fit any platform
The integration the workflow depends on does not exist natively on any platform. The logic requires real-time processing with sub-second response times. The business rules are complex enough that a visual workflow editor becomes a maintenance liability. Custom automation built in Python or TypeScript, hosted as a lightweight service, often outperforms platform-based approaches for these cases, at a higher build cost but lower operating cost.
Common questions
What European teams ask when choosing an automation platform.
Is Zapier GDPR-compliant for European companies?
Zapier has a GDPR-compliant data processing agreement and is certified under the EU-US Data Privacy Framework. However, data is processed on US servers. For workflows involving sensitive personal data in regulated sectors, this may not satisfy your specific GDPR obligations. Make offers EU data processing for paid plans. n8n self-hosted gives you full control. Get your Data Protection Officer involved before running personal data through any third-party automation platform.
What is the real cost of Zapier at scale?
Zapier pricing is based on "tasks" (each action in a Zap counts as one task). At 10,000 tasks per month the Professional plan costs around €150 to €200. At 100,000 tasks per month you are looking at €500 to €800. If your automations run at volume, Make typically costs 60 to 80 percent less. n8n self-hosted eliminates per-task cost entirely.
Can non-technical teams use Make?
Yes, but with a steeper learning curve than Zapier. The visual scenario builder is intuitive for simple flows. Branching logic, error handling, and data transformation require a few hours of learning. Most technical operations staff can get productive in Make within a day. The complexity ceiling is significantly higher than Zapier, so it stays usable as workflows grow.
When does it make sense to build automation from scratch?
When the workflow requires real-time response (under 500ms), when it integrates with a system that has no API compatible with these platforms, when the business logic is too complex to maintain visually, or when the data security requirements prohibit any third-party processing. Custom builds also make sense when you want full ownership of the automation logic without vendor dependency.
How do I migrate from Zapier to Make or n8n?
There is no automated migration path. Each workflow needs to be rebuilt natively in the new platform. For most companies, the approach is: audit which Zaps are actually running and valuable (many are dormant), rebuild the high-value ones first in the new platform, run both in parallel for two to four weeks, then switch off Zapier. Budget one to two days of technical time per 10 to 15 workflows of moderate complexity.
How we approach automation at SomeTech.work
We start from the workflow, not the platform.
The first question we ask is not which tool to use. It is: what exactly runs by hand today, how many times per week, and what breaks when it goes wrong? The answer determines whether a platform like Make or n8n is right, or whether a custom-built service is the cleaner answer. See how we scope and deliver AI and automation workflows for European companies.
**We do not recommend platforms that create lock-in where it is not necessary.** For high-volume workflows or regulated data, we typically recommend n8n self-hosted or a custom build. For simpler connections between standard SaaS tools, we use Make. Either way, the workflow is documented, tested against real data before production cutover, and handed over with a named exception owner, not just a workflow diagram.
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