Key takeaways
- Zapier is the fastest to start but the most expensive to scale — costs explode past 5,000 tasks/month.
- Make offers better visual logic and more affordable mid-volume pricing, but lacks native AI agent nodes and code execution.
- n8n wins at enterprise scale: self-hostable, no per-operation pricing, native AI agent architecture, and full code node support.
- For data-sensitive industries (legal, finance, healthcare), n8n self-hosted is the only option that keeps data fully within your infrastructure.
- The right choice depends on team technical depth, data sovereignty requirements, and monthly automation volume — not which tool has the most integrations.
The Real Question Is Not Features — It Is Economics and Architecture
Every comparison of n8n, Make, and Zapier defaults to listing integrations and showing feature matrices. That misses the point. All three platforms can connect your CRM to your email tool. The question that actually matters for a business making a long-term infrastructure decision is: what does this cost at 100,000 operations per month, what happens when you need an AI agent, and what do you do when your data cannot leave your infrastructure?
This guide answers those questions with real numbers, not marketing copy.
Platform Architecture: What You Are Actually Buying
Zapier
Zapier is a task-execution platform built around "Zaps" — event-trigger-to-action pairs. Its architecture is fundamentally linear: one trigger, one or more sequential actions. Multi-step Zaps with branching logic exist but become unwieldy past moderate complexity. Zapier's core value proposition is the breadth of its integration library (7,000+ apps) and the speed of onboarding — a non-technical user can build a working automation in 15 minutes.
What Zapier is not: a platform for complex, stateful workflows, AI agents, or high-volume data processing. Its "Interfaces" and "Tables" products are bolted-on additions that have not yet matured to production quality. Zapier AI is limited to pre-built AI actions; there is no native agent framework.
Make
Make (formerly Integromat) uses a visual scenario editor built around modules connected in a flow graph. It supports complex routing, iterators, aggregators, and multi-path branching in a way Zapier cannot match visually. The operations-based pricing model (rather than task-based) means you can run more complex, multi-step scenarios for the same cost.
Make is strong for operations and marketing automation teams that need visual complexity without code. Where it falls short: no native code execution (you cannot run arbitrary JavaScript or Python inside a scenario), limited AI agent capabilities, and no self-hosting option. All data routes through Make's cloud infrastructure.
n8n
n8n is a workflow automation platform with an open-source core and a cloud-hosted option. Its architecture differs from Zapier and Make in three fundamental ways: it has native code nodes (JavaScript and Python execute directly in the workflow), it has a built-in AI agent framework (LangChain-compatible, with direct nodes for OpenAI, Anthropic Claude, Gemini, and open-source models), and it can be self-hosted on any infrastructure — meaning your data never leaves your network.
n8n's cloud pricing is per-workflow-execution rather than per-operation, which changes the economics significantly at scale. The trade-off: steeper learning curve, and the integration library (400+ native integrations) is smaller than Zapier's, though HTTP Request nodes cover virtually any REST API.
Pricing at Scale: The Number That Changes Everything
Most comparisons show the entry-level pricing. Here is what each platform costs at meaningful business scale:
| Volume | Zapier | Make | n8n Cloud | n8n Self-Hosted |
|---|---|---|---|---|
| 2,000 tasks/ops/month | $73.50/mo | $9/mo | $20/mo | $0 + server cost |
| 10,000 tasks/ops/month | $363/mo | $16/mo | $20/mo (executions, not ops) | $0 + server cost |
| 50,000 tasks/ops/month | $799/mo+ | $29/mo | $50/mo | $0 + server cost |
| Unlimited | Enterprise pricing | Enterprise pricing | Enterprise pricing | $0 + server cost |
The pricing model difference is critical: Zapier charges per task (each action in a multi-step Zap counts as one task). A 10-step Zap running 1,000 times = 10,000 tasks. Make charges per operation (similar to tasks). n8n Cloud charges per workflow execution — a 50-step workflow running 1,000 times = 1,000 executions. At high step-count workflows, n8n's economics are dramatically better.
AI Agent Capabilities: The Emerging Differentiator
As businesses move from simple task automation to multi-step AI agents — systems that can reason, use tools, and make decisions — the gap between platforms widens significantly.
| Capability | Zapier | Make | n8n |
|---|---|---|---|
| Native AI agent nodes | Limited (pre-built actions) | No | Yes (LangChain-compatible) |
| Anthropic Claude integration | HTTP only | HTTP only | Native node |
| Memory / conversation state | No | No | Yes (built-in) |
| Tool use / function calling | No | No | Yes |
| Code execution in workflow | No | No | Yes (JS + Python) |
| Vector store integration | No | No | Yes (Pinecone, Supabase, Qdrant) |
| Sub-agent orchestration | No | No | Yes |
If you are building AI agents — systems that use language models to execute multi-step tasks, call tools, and maintain context — n8n is the only platform in this comparison with native support for the full agent loop. Make and Zapier require HTTP Request nodes and custom code to approximate what n8n provides out of the box.
Data Sovereignty: The Non-Negotiable for Regulated Industries
For legal firms, financial services companies, healthcare providers, and any organisation handling sensitive client data, the question of where data flows during automation is not optional — it is a compliance requirement.
- Zapier: Cloud-only. All data routes through Zapier's US-hosted infrastructure. No self-hosting option. GDPR-compliant under their DPA, but data still leaves your network.
- Make: Cloud-only. EU data centres available, but no self-hosting. Same fundamental constraint.
- n8n: Can be deployed on your own server, VPC, or Kubernetes cluster. Data never leaves your infrastructure. This is the only option where you have true data sovereignty — no third-party cloud processes your workflow data.
For Chronexa clients in legal, finance, and professional services, we recommend n8n self-hosted as the default architecture for any automation touching client data. The infrastructure overhead is manageable (a $40/month VPS handles most SME workloads), and the compliance benefit is unambiguous. See our enterprise AI solutions for how we architect this for regulated sectors.
When to Choose Each Platform
Choose Zapier if:
- Your team is non-technical and needs to build automations without any code knowledge
- You need breadth of integrations fast (Zapier's 7,000+ app library is unmatched)
- Your automation volume is under 2,000 tasks/month and you value simplicity over cost
- You are automating simple, linear workflows (form submission → CRM update → email)
Choose Make if:
- You need complex visual branching logic that non-developers can still understand
- Your volume is 10,000–100,000 operations/month and you want to stay off enterprise pricing
- You need the router/iterator/aggregator pattern for data transformation
- Your team is comfortable with Make's steeper-than-Zapier but flatter-than-n8n learning curve
Choose n8n if:
- You are building AI agents (mandatory — n8n is the only viable option here)
- Your data cannot leave your infrastructure (regulated industry, client confidentiality)
- Your automation volume is high (1,000+ complex workflow executions/month)
- Your team has engineering capability and wants a platform that does not limit what they can build
- You need custom code execution, complex data transformation, or sub-workflow orchestration
The Hybrid Reality
Most mature automation stacks do not pick one platform and use it exclusively. A common enterprise pattern: Zapier for the long tail of simple, one-off departmental automations (because onboarding new teams is fast), Make for the operations team's mid-complexity reporting and CRM sync workflows, and n8n as the backbone for AI agent pipelines, data-sensitive processes, and high-volume production workflows.
The mistake is trying to use Zapier or Make for the AI agent use cases where n8n is architecturally the right answer. Retrofitting agent capabilities onto a task-execution platform creates fragile, expensive workarounds that break in production.
Frequently Asked Questions
Is n8n really free to self-host?
Yes — the community edition of n8n is open-source under a fair-code licence, free to self-host with no workflow execution limits. The cloud-hosted version (n8n.cloud) is paid. Most enterprise deployments use self-hosted n8n on their own infrastructure for cost and sovereignty reasons.
Can I migrate from Zapier to n8n without rebuilding everything?
There is no automated migration tool. Workflows must be rebuilt in n8n. The rebuild is typically faster than building from scratch because you already know the logic — most teams estimate 30–50% of the time of the original build. The economic incentive to migrate grows quickly past 5,000 tasks/month on Zapier.
How difficult is n8n to set up and maintain?
n8n self-hosted on a VPS requires basic Docker knowledge and a one-time setup of roughly 2–3 hours. Ongoing maintenance is minimal — version upgrades are straightforward, and the platform is stable in production. For organisations without internal technical capacity, n8n Cloud removes the infrastructure overhead entirely.
Does Make support AI agents?
Make has HTTP modules that can call OpenAI, Anthropic, and other AI APIs, but it does not have native agent nodes — no built-in memory, tool-use framework, or agent loop. You can approximate simple AI actions in Make, but building production AI agents requires significant custom work that n8n handles natively.