Spec comparison
| Spec | n8n | Zapier |
|---|---|---|
| License | Sustainable Use (source-available) | Closed SaaS |
| Self-host | Yes (free) | No |
| Cloud entry price | $24/mo (Starter) | $19.99/mo (Starter) |
| Pricing model | Per workflow execution | Per task (single step) |
| Integrations | 1,200+ nodes | 6,000+ apps |
| Code nodes | JS + Python (full) | JS only (sandboxed) |
| AI / LLM nodes | Native LangChain support | AI-native via Copilot/Actions |
| Audience | Devs, technical operators | Non-technical operators |
| Best for | Self-host, dev-grade automation | Breadth of integrations, ease |
Feature matrix
| Capability | n8n | Zapier |
|---|---|---|
| Self-host (free tier) | ✓ | ✗ |
| Visual workflow builder | ✓ | ✓ |
| Code nodes (JS) | ✓ | ✓ |
| Code nodes (Python) | ✓ | ✗ |
| 6,000+ pre-built integrations | ✗ | ✓ |
| LangChain / AI agent native | ✓ | ~ |
| Webhooks (custom) | ✓ | ✓ |
| Loops / branching logic | ✓ | ~ |
| Sub-workflows / reusable modules | ✓ | ✗ |
| Version control via git | ✓ | ✗ |
| On-prem deployment | ✓ | ✗ |
| SOC 2 / HIPAA (n8n: Enterprise tier only) | ~ | ✓ |
| No-code friendly UI | ~ | ✓ |
| Tables / built-in storage | ✓ | ✓ |
| Per-task pricing | ✗ | ✓ |
| Per-execution pricing | ✓ | ✗ |
Cost analysis
Cost depends on workflow complexity. Zapier charges per task (one app action = one task) so a 10-step Zap consumes 10 tasks per run. n8n charges per workflow execution, regardless of step count.
| Volume / shape | n8n cloud | n8n self-host | Zapier |
|---|---|---|---|
| 5K simple Zaps/mo (2 steps) | $24 | ~$10 (VPS) | $49 |
| 10K complex workflows (10 steps) | $60 | ~$10 | $399 (100K tasks) |
| 100K runs (5 steps) | $240 | ~$40 | $2,000+ (custom) |
| 1M runs (5 steps) | $1,200+ | ~$200 | Enterprise quote |
When n8n wins
n8n wins anywhere a developer is the primary builder. Self-hosting is free, runs in a single Docker container with PostgreSQL, and scales to hundreds of thousands of executions per month on modest infrastructure. Code nodes support full JavaScript and Python with arbitrary npm/pip packages: this alone unlocks workflows that are impossible in Zapier's sandbox. Per-execution pricing means a 10-step workflow costs the same as a 1-step, so complex automation does not penalize you. Native LangChain support makes n8n one of the cleanest places to build a custom AI agent without writing a framework yourself. Sub-workflows let you build reusable modules. Git versioning lets you treat automation like real code. For any team with engineering bandwidth and a need for serious automation scale, n8n is the right default, and the self-host story makes it the only credible option for sovereignty-bound deployments.
When Zapier wins
Zapier wins on integration breadth and operator-friendly UX. 6,000+ apps means whatever obscure SaaS your marketing team uses, there is probably already a Zap. Setup time for a typical 2-3 step Zap is measured in minutes, not hours, and non-technical users can build and maintain workflows without engineering involvement. The Copilot AI assistant is genuinely useful for translating "I want X to happen when Y" into a working Zap. AI Actions and Tables make Zapier a real platform for ops teams doing lightweight AI work. The reliability story is excellent: Zapier handles retries, dead-letter queues, and rate limits invisibly. For RevOps, marketing ops, customer success, and any function that does not have engineering as a hard dependency, Zapier is the right default. The cost premium is the price of not needing engineers in the loop.
The common combination
Many companies run both. Zapier for the operator-built workflows in marketing, sales ops, and customer success (where the ROI is "don't need to ask engineering." n8n self-hosted for the engineering-built backbones) internal automations, AI agents, ETL-adjacent jobs, anything where execution volume or complexity would make Zapier prohibitively expensive. Many teams hand workflows off from Zapier to n8n once volume justifies it. If you are routing AI traffic inside an automation, the Swfte router works as a single LLM endpoint inside either platform.
How to choose
- Map your builders. If non-technical operators own automation, lead with Zapier. If engineers own it, lead with n8n.
- Estimate monthly run volume × steps per run. If task count exceeds 10K-20K, n8n wins on cost.
- Audit required integrations. If anything obscure is missing from n8n's 1,200, you may need Zapier or a custom HTTP node.
- Decide on hosting model first. Self-host n8n if compliance demands it; otherwise cloud is fine for both.
- Pilot a single high-value workflow on each. Measure build time, runtime cost, and ops overhead.
- Keep a migration option open. Both can run side by side; do not lock in until you know the volume profile.
Frequently asked questions
Is n8n or Zapier better in 2026?
Different audiences. n8n wins for technical teams who need self-hosting, Python code nodes, or per-execution pricing that does not balloon at scale. Zapier wins for non-technical operators and teams that need 6,000+ integrations out of the box without engineering time.
Which is cheaper at scale?
n8n by a wide margin once you cross ~10K workflow runs/month. Self-hosting is free; cloud is per-execution rather than per-task, so a 10-step workflow costs the same as a 1-step. Zapier's per-task model penalizes complex workflows. For simple 1-2 step automations under 1K/mo, Zapier's starter plan is competitive.
Can I self-host n8n in production?
Yes. The Sustainable Use license permits internal/SaaS-adjacent use without a paid license; full enterprise terms apply if you embed it in a paid product. Most teams run n8n on a single Docker container with PostgreSQL: works for 100K+ executions/month.
Which has better AI / LLM agent support?
n8n has had native LangChain agent nodes since 2024 and is the more flexible canvas for building custom agents. Zapier has Copilot and AI Actions which are great for non-technical users but less customizable. For coded agent flows, n8n wins.
Can I migrate from Zapier to n8n?
Yes. There is no automated import: you rebuild Zaps as n8n workflows. The conceptual mapping is direct (trigger + actions). Most teams report 50-70% lower runtime cost after migration. Plan ~1 day of engineering per 20-30 active Zaps.