n8n vs Make: Self-Hosted vs Cloud Automation Compared
n8n vs Make 2026 — self-hosted open-source automation vs cloud iPaaS: pricing, AI nodes, integrations, and which workflow tool scales better.
Quick Answer
n8n 2.0 wins for teams wanting self-hosted, unlimited workflows with AI nodes (LangChain, OpenAI, vector stores) at zero marginal cost per execution. Make wins for non-technical users who need 1,000+ pre-built integrations, a visual bubble-and-line interface, and a $9/month cloud plan with no infrastructure to manage. Use n8n if you can host Docker; use Make if you want plug-and-play SaaS automation.
n8n vs Make: Overview
Developers, DevOps teams, AI automation pipelines, data-sensitive workflows
Self-hosted: unlimited workflows, executions, and users — free forever
Cloud: €20/month (2,500 executions/month); Enterprise: custom
n8n vs Make: Feature Comparison
| Feature | n8n | Make |
|---|---|---|
| Self-Hosted Option | Yes — Docker, unlimited executions free | No — cloud-only |
| Native AI / LangChain Nodes | Yes — full AI agent nodes in n8n 2.0 | Basic OpenAI wrapper modules only |
| Integration Count | ~400 native nodes | 1,000+ pre-built integrations |
| Cloud Entry Price | €20/month (2,500 executions) | $9/month (10,000 operations) |
| Non-Technical UX | Moderate — expression syntax required | Easy — visual bubble-and-line canvas |
| Execution Cost at Scale | Free on self-hosted — unlimited | Operations-based — costs scale with volume |
Pros & Cons
n8n
Pros
- n8n 2.0 AI nodes (Jan 2026): LangChain chains, OpenAI/Anthropic calls, vector store upsert, and memory all as native nodes
- Self-hosted free: Docker deploy in 5 minutes — unlimited workflows, users, and executions at $0/month infra cost
- Code node: JavaScript and Python inline — escape no-code constraints without leaving the workflow
- 400+ integrations with sub-expression templating — map nested JSON paths without extra transform nodes
- Webhook triggers: custom headers, query params, and response shaping — no third-party relay needed
Cons
- Self-hosting overhead: Docker updates, SSL certs, and uptime monitoring are your responsibility
- Cloud plan: €20/month cap at 2,500 executions — exceeding it requires upgrading or self-hosting
- UI learning curve: expression syntax (`{{ $json.field }}`) confuses non-developers for 3–5 hours
- Fewer integrations than Make: ~400 native nodes vs Make's 1,000+ — some niche SaaS require HTTP node workarounds
Make
Pros
- 1,000+ pre-built app integrations — covers most niche SaaS without custom HTTP calls
- Visual scenario builder: drag bubble modules onto canvas — readable flow diagrams even non-developers understand
- Data store: built-in key-value database for storing state between scenario runs without external DB
- Error handling: dedicated error-handler modules with retry, ignore, rollback, and break paths
- Affordable entry: $9/month Core plan covers 10,000 operations — enough for most small business automations
Cons
- No self-hosting: Make is SaaS-only — data always passes through Make's EU/US cloud infrastructure
- Operations model: complex scenarios burn operations fast (each module = 1 op) — 10K ops exhausted in one large run
- AI nodes limited: Make AI modules wrap OpenAI API but lack LangChain chains, vector stores, and agent memory
- Scenario limits: free plan caps at 2 active scenarios — upgrading to run >2 automations simultaneously requires paid plan
Our Verdict: n8n vs Make
Use n8n if you run Docker and need AI-native automation (LangChain agents, vector store pipelines, OpenAI tool calls) without paying per execution — n8n 2.0's AI nodes are the best no-code AI automation layer in 2026. Use Make if you're a non-technical user, agency, or e-commerce operator who needs 1,000+ plug-and-play integrations, a visual canvas your client can read, and a $9/month cloud plan with no server to manage. The decision is simple: if you have a developer on the team, n8n self-hosted is free and more powerful; if you don't, Make's cloud UX justifies the operations cost.
n8n vs Make — FAQs
How do n8n AI nodes compare to Zapier's AI features in 2026?
n8n 2.0's AI nodes are significantly more capable than Zapier's AI steps. n8n supports full LangChain chain construction, multiple LLM providers (OpenAI, Anthropic, Google, Ollama), vector store nodes (Pinecone, Supabase pgvector, Qdrant), and persistent agent memory — all as drag-and-drop nodes. Zapier's AI features are limited to OpenAI text generation, summarization, and extraction within a Zap step. For multi-step AI agents, RAG pipelines, or tool-calling workflows, n8n is the only no-code/low-code platform that handles them natively in 2026.
Can Make handle high-volume automation like 100,000 operations per month affordably?
At 100,000 operations per month, Make's pricing becomes significant. The Teams plan at $29/month includes 10,000 operations — you'd need the 100K operations add-on, bringing total cost to approximately $229/month. At that volume, n8n self-hosted on a $6/month VPS (Hetzner CX22) runs the same workflows at zero marginal cost per execution. The Make advantage (ease of use, 1,000+ integrations) needs to be worth $200+/month vs n8n hosting costs. For most high-volume automation teams above 50,000 operations/month, n8n self-hosted has better unit economics.
Is n8n reliable enough for production automation in 2026?
Yes — n8n is used in production by thousands of companies including Fortune 500 firms. The self-hosted version has built-in retry logic, execution history (90-day retention), error workflows, and webhook queue persistence. For production deployments, the recommended setup is n8n on Docker with PostgreSQL (not SQLite), a reverse proxy (Nginx/Caddy), and an external Redis instance for queue mode — total infrastructure cost is under $20/month on Hetzner. n8n Cloud (€20/month) offers 99.9% uptime SLA and removes all infrastructure management. The main production risk is self-hosting: if your server goes down, workflows pause until it restarts.
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