Three pricing models, three philosophies, one decision. Real cost breakdown at 100k operations/month and the criteria we use to recommend one over the other.
We've built production workflows on all three. This is our honest breakdown.
Pricing Models
All three platforms charge differently. The model matters more than the headline price — a complex 20-step workflow can cost 20× more on Zapier than n8n for the same number of runs.
One workflow run = 1 execution, regardless of how many nodes it touches. A 50-node workflow running 5,000 times = 5,000 executions.
Best for complex, multi-step workflows at high volume.
Cloud from $50/mo (10k executions). Self-hosted: free.
Each module step = 1 operation. A 20-module scenario running 5,000 times = 100,000 operations. More granular than Zapier tasks.
Best for moderate-complexity workflows at moderate volume.
From $9/mo (10k ops). Additional ops at $9/10k.
Each action step = 1 task. A 20-action Zap running 5,000 times = 100,000 tasks. Triggers are usually free; actions are counted.
Best for simple 2–3 step automations at low volume.
From $19.99/mo (750 tasks). Scales steeply with volume.
Real Cost Example
Scenario: 20 workflow steps per run, 5,000 runs per month = 100,000 step-level operations. This is typical for a mid-size ops team running daily automations across Salesforce, Slack, and a database.
The bottom line
The same workload costs 8–12× more on Zapier than Make, and 20–30× more than n8n. A team spending $500/month on Zapier can run the same workflows on n8n self-hosted for $20/month — saving $5,760/year. The gap widens further as volume grows, because n8n's per-execution model doesn't multiply with workflow complexity.
AI Agent Depth
Make and Zapier can call LLM APIs via HTTP modules — but they don't have an agent primitive. n8n ships a native AI Agent node that reasons, remembers, and calls other workflow nodes as tools.
If your automation needs an LLM to decide what to do, loop until a condition is met, or use retrieved context from a vector store — n8n is the only realistic choice of the three. Make and Zapier are linear workflow tools; n8n is becoming an agent orchestration platform.
Feature Comparison
✓ Full support · ~ Partial / workaround · ✗ Not supported
| Feature | n8n | Make | Zapier |
|---|---|---|---|
Open-source / self-hostable n8n community edition is free and self-hostable; Make and Zapier are cloud-only SaaS | ✓ | ✗ | ✗ |
Native AI agent node n8n has a native Agent node with memory, tool use, and LangChain; others route through HTTP to LLM APIs | ✓ | ~ | ~ |
Visual flow canvas Make's canvas is the best designed; n8n is a functional node graph; Zapier is a linear step list | ~ | ✓ | ✗ |
Integration count Zapier has the most apps; all three cover the common SaaS stack; n8n fills gaps with HTTP/webhook nodes | 422+ | 2,000+ | 7,000+ |
JavaScript & Python code nodes n8n supports both JS and Python natively; Make and Zapier have limited JavaScript only | ✓ | ~ | ~ |
Pricing model Execution = entire workflow run; operation = each module step; task = each action step | Per execution | Per operation | Per task |
Error handling & retry logic n8n and Make have proper error branches and retry config; Zapier error handling is limited | ✓ | ✓ | ~ |
Workflow versioning / rollback n8n and Make support version history and rollback; Zapier does not have rollback | ✓ | ✓ | ✗ |
HIPAA / on-prem data control Self-hosted n8n gives full data sovereignty and PHI control; Make and Zapier are US-hosted SaaS | ✓ | ✗ | ✗ |
Human-in-the-loop / approval n8n has wait-for-webhook approval nodes; Make has limited approval flows; Zapier has none natively | ✓ | ~ | ✗ |
Sub-workflows / modularity n8n and Make support calling workflows from within workflows; Zapier Paths is more limited | ✓ | ✓ | ~ |
Free tier n8n self-hosted is free forever; Make and Zapier free tiers are trial-level usage only | Unlimited (self-host) | 1,000 ops/mo | 100 tasks/mo |
Decision Matrix
There is no universally right answer — each platform wins in a specific context.
When control, cost, and AI depth matter more than time-to-first-automation.
When your team needs the best UX and 2,000+ integrations without code.
When the specific app you need is only on Zapier or the team values zero friction.
Our default recommendation
For teams building AI-powered workflows or running high-volume automation, n8n is the strongest long-term choice — the open-source model, per-execution pricing, and native AI agent capabilities create durable cost and capability advantages. For non-technical teams that need to move quickly without a dedicated engineer, Make is the best designed option at a fraction of Zapier's cost. Zapier is right when app coverage is the deciding factor.
Our Role
Hestur AI builds production workflow automation on n8n, Make, and Zapier. We choose the platform based on your team structure, volume, and whether AI agent depth is a requirement.
Our preferred platform for any AI-native automation work. We architect n8n self-hosted deployments, build multi-agent pipelines with LangChain and vector store memory, and integrate with RAG systems for document-aware workflows.
AI agent orchestration, document processing, high-volume data pipelines, HIPAA-compliant healthcare workflows.
Common for RevOps and marketing clients who have non-technical operations teams. We set up the Make infrastructure, build the complex scenarios, then hand off to the client's team to manage via the visual canvas.
Sales automation, marketing ops, CRM sync, e-commerce order workflows, reporting pipelines.
We build on Zapier when a client already has Zapier in their stack and the use case is straightforward enough that migrating isn't worth the friction. We also help teams audit Zapier costs and recommend migration paths to n8n when the ROI case is clear.
Legacy Zap audits, cost-reduction migrations to n8n, simple trigger-action automations.
Book a 30-minute call. We'll review your existing stack, workflow complexity, and team structure — and give you a clear platform recommendation backed by a cost projection.