Open-source self-hosted powerhouse vs polished cloud automation — we break down pricing, AI workflows, ease of use, and who each platform is really for.
The workflow automation space has two serious contenders for technical users in 2026: n8n and Make (formerly Integromat). Both use a visual canvas approach. Both handle complex branching logic. Both have solid AI integrations. But they diverge sharply on cost model, hosting philosophy, and who they're built for.
n8n has exploded in popularity as the go-to choice for developers, agencies, and AI builders who want full data ownership and zero per-execution fees. Make remains the polished, cloud-first alternative — easier to get started, broader app library, and no server management required.
After building real workflows on both platforms, here's the honest breakdown for 2026.
Unmatched value when self-hosted — unlimited workflows, executions, and users for the cost of a VPS. The best AI agent builder in the automation space.
The most polished visual automation platform for users who don't want server management. Stronger app library, smoother UX, lower barrier to entry.
Bottom line: n8n wins on power, cost at scale, and AI capabilities. Make wins on ease of use and app coverage. If you're comfortable with basic server setup, n8n is the better long-term investment — by a significant margin.
| Feature | n8n | Make |
|---|---|---|
| Free plan | ✓ Self-hosted (unlimited) | 1,000 ops/month |
| Starting paid price (cloud) | $20/month (2,500 executions) | $9/month (10,000 operations) |
| Self-hosting | ✓ First-class support | ✗ Cloud only |
| Visual canvas builder | ✓ Node-based canvas | ✓ Scenario canvas |
| Code nodes (JS/Python) | ✓ Built-in, powerful | Limited (HTTP modules only) |
| AI Agent nodes | ✓ Native AI Agent + LangChain | ✓ OpenAI + HTTP modules |
| LLM integrations | OpenAI, Claude, Gemini, Ollama, Mistral | OpenAI, Claude, Gemini |
| Local LLM support (Ollama) | ✓ Native node | ✗ Manual HTTP only |
| RAG / vector store nodes | ✓ Pinecone, Qdrant, Supabase | Manual HTTP modules |
| Branching / conditional logic | ✓ Advanced IF/Switch nodes | ✓ Advanced routers |
| Error handling | ✓ Full error workflows | ✓ Full control |
| App integrations (native) | 400+ | 1,500+ |
| HTTP / webhook | ✓ All plans | ✓ All plans |
| Data ownership | ✓ Full (self-hosted) | Cloud-only (Make's servers) |
| Learning curve | Moderate–High | Moderate |
| Best for | Devs, agencies, AI builders, scale | Non-technical teams, cloud-first users |
Both tools use a visual node-based canvas — but the experience is meaningfully different.
Make's canvas feels more polished. Nodes snap together cleanly, the color-coding is consistent, and the error states are obvious. Make has invested heavily in UX and it shows — setting up a 5-step scenario with a form trigger, data transformation, and email notification takes about 10 minutes for a first-time user.
n8n's canvas is powerful but rawer. The node library is more scattered, search is your best friend, and the settings panels can be dense. That said, n8n has closed the gap significantly in 2025–2026. The new canvas redesign is cleaner, templates are more discoverable, and the AI assistant for building workflows is genuinely useful.
Once you're past the learning curve, n8n's canvas handles larger workflows better. 50-node workflows that would feel cluttered in Make remain navigable in n8n thanks to better zoom controls, sticky notes, and workflow organization features.
Make's onboarding is smoother, its error messages are clearer, and its documentation is more comprehensive for beginners. For a non-technical user who needs to be productive in a day, Make is the right call.
Ready to learn automation properly?
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Explore DataCamp Courses →Both tools are genuinely powerful for complex automation — but they take different approaches to extensibility.
n8n's Code node lets you write JavaScript or Python directly inside your workflow. This isn't a workaround — it's a first-class feature. You can manipulate data structures, call custom functions, use npm packages, and handle edge cases that would require multiple modules in Make. For developers, this changes everything.
Make matches n8n on the visual logic side — routers, iterators, aggregators, and error handlers are all excellent. Where Make falls short is when you need to go beyond what the UI offers. Custom logic in Make requires either a clever combination of modules or accepting limitations that n8n simply doesn't have.
This is where n8n has established a clear lead, and it's arguably the most important differentiator in 2026.
n8n built a dedicated AI Agent node with LangChain integration that lets you construct multi-step AI agents visually. It's not just "call OpenAI and get a response" — you can wire in memory, tools, RAG pipelines, and multi-agent chains all within the same workflow canvas.
💡 Real example: You can build a customer support agent in n8n that routes incoming emails, searches your knowledge base (RAG), drafts a response with Claude, waits for human approval on flagged tickets, and logs everything to Airtable — all in a single workflow, running on your own server, at effectively zero marginal cost.
Make supports OpenAI, Anthropic, and Google AI via dedicated modules. For standard use cases — summarize this text, classify this input, generate this content — Make works well. The gap shows when you need chained AI agents, memory, or custom tool calling. Make handles these through HTTP module workarounds, but the experience is significantly more manual than n8n's native AI nodes.
Need a reliable server to self-host n8n?
DigitalOcean's $6/month Droplet runs n8n smoothly for most use cases. One-click Docker install, predictable pricing, and no vendor lock-in.
Try DigitalOcean — $200 Free Credit →Make has a significant edge here: 1,500+ native integrations vs n8n's 400+. For popular tools (Slack, Gmail, Notion, Airtable, HubSpot, Shopify), both platforms have solid coverage. The gap shows with niche SaaS tools — Make often has a dedicated module where n8n requires a generic HTTP node.
| Category | n8n | Make |
|---|---|---|
| Google Workspace | ✓ Full suite | ✓ Full suite |
| Microsoft 365 | ✓ Core apps | ✓ Full suite |
| CRM (HubSpot, Salesforce) | ✓ Both | ✓ Both + more |
| E-commerce (Shopify, WooCommerce) | ✓ Both | ✓ Both + more |
| Dev tools (GitHub, Jira, Linear) | ✓ Strong coverage | ✓ Strong coverage |
| Niche SaaS tools | HTTP fallback | ✓ Often native |
| Custom API / Webhook | ✓ Excellent | ✓ Excellent |
| Local / self-hosted apps | ✓ Full access | Limited (cloud-only) |
| Database nodes (Postgres, MySQL) | ✓ Native | Via data stores only |
| File system access | ✓ Self-hosted | ✗ |
The practical gap is smaller than the numbers suggest. n8n's HTTP Request node is powerful enough to integrate with virtually any API, and for technical users, writing a quick API call is often faster than navigating a pre-built module's settings panel anyway.
This is the section that changes the calculus for a lot of users.
n8n is open-source under a fair-code license, which means you can self-host it on any server and run unlimited workflows, unlimited executions, and unlimited users — for free (beyond the server cost).
On a $6/month DigitalOcean Droplet (1 vCPU, 1GB RAM), n8n runs comfortably for most individual and small-team workloads. Getting it running takes about 20 minutes with Docker:
For larger workloads, n8n supports horizontal scaling via queue mode with Redis and worker instances — the kind of infrastructure that would cost hundreds of dollars per month on any SaaS automation platform.
An agency running 50,000 workflow executions per month would pay approximately:
| Platform | 50K executions/month | Annual cost |
|---|---|---|
| n8n self-hosted (DigitalOcean $12/mo droplet) | $12/month | ~$144/year |
| n8n Cloud (Pro plan) | ~$50/month | ~$600/year |
| Make (Teams plan) | ~$159/month | ~$1,900/year |
| Zapier (Professional) | ~$299/month | ~$3,588/year |
The numbers speak for themselves. Self-hosted n8n isn't just cheaper — for technical teams, it's essentially a different category of tool.
The best managed cloud hosting for your n8n server
Cloudways makes VPS management approachable for non-sysadmins — managed security, backups, and one-click server provisioning on DigitalOcean, Linode, or Vultr infrastructure.
Try Cloudways Free for 3 Days →| Plan | Price | Executions | Users |
|---|---|---|---|
| Self-hosted (Community) | Free | Unlimited | Unlimited |
| Cloud Starter | $20/month | 2,500/month | 2 |
| Cloud Pro | $50/month | 10,000/month | 5 |
| Cloud Enterprise | Custom | Custom | Unlimited |
| Self-hosted Enterprise | Custom | Unlimited | Unlimited |
| Plan | Price | Operations/month | Users |
|---|---|---|---|
| Free | $0 | 1,000 | 1 |
| Core | $9/month | 10,000 | 2 |
| Pro | $16/month | 10,000 + more ops available | 3 |
| Teams | $29/month | 10,000 + more ops available | Unlimited |
| Enterprise | Custom | Custom | Unlimited |
⚠️ Key distinction: n8n counts "executions" (one full workflow run = 1 execution). Make counts "operations" (each module step = 1 operation). A 5-step Make scenario uses 5 operations per run. Compare carefully when evaluating plans — n8n's Cloud plans are pricier per execution count, but self-hosted eliminates the equation entirely.
→ n8n (self-hosted). Code nodes + full API access + free at scale = no-brainer for technical builders.
→ n8n. Native AI Agent node, LangChain integration, local LLM support, and vector stores make it the clear choice.
→ n8n (self-hosted if technical). Unlimited client workflows at ~$12/month vs hundreds of dollars on Make or Zapier.
→ Make. No server stress, clean UI, native integrations for common tools, and reasonable pricing for typical volumes.
→ Make. Better CRM and marketing tool integrations out of the box, plus easier onboarding for a non-dev team.
→ n8n (self-hosted). Embed workflows in your product stack, connect internal databases, keep costs minimal as you scale.
If you have any technical background — you've used a terminal, set up a VPS, or written a bit of code — n8n self-hosted is the best automation tool available in 2026. The cost savings at scale are dramatic, the AI agent capabilities are genuinely ahead of everything else, and the code nodes give you an escape hatch that no SaaS tool can match.
If you want to get started today without touching a server, Make is the best cloud automation platform. It's more polished than Zapier, significantly cheaper, and handles everything most small-to-medium teams need.
The honest advice: start with Make's free plan to learn automation concepts, then migrate to self-hosted n8n once you're ready to scale or need AI agent capabilities. Many teams follow exactly this path.
If neither fully fits, here are strong alternatives:
For more options, see our full roundup: 7 Best No-Code AI Automation Tools in 2026.
n8n is better than Make if you want full data ownership, zero per-execution costs, and leading AI agent capabilities. Make is better for users who want a polished cloud platform with no server setup and a broader app library. Technical teams lean toward n8n; non-technical users lean toward Make.
n8n's self-hosted version is free under a fair-code license — unlimited workflows, executions, and users at no cost on your own server. You just pay for the server ($6–$12/month on DigitalOcean). The cloud-hosted version starts at $20/month.
Yes, for most use cases. n8n covers the same automation territory and adds code nodes for custom logic. The trade-off is setup complexity. If you're comfortable with basic server management, n8n can replace Make and eliminate recurring SaaS costs entirely.
n8n has become a leading platform for AI agent workflows. Its AI Agent node supports OpenAI, Claude, Gemini, and local Ollama LLMs. LangChain integration enables RAG pipelines, multi-agent chains, and memory-enabled workflows — capabilities Make handles but requires significantly more manual HTTP work to replicate.
The main downsides are: (1) self-hosted setup requires server knowledge, (2) steeper learning curve than Make, (3) smaller native app library (400+ vs 1,500+), (4) community support rather than fully polished official docs for some features. For non-technical users, these barriers are real.
Self-hosted n8n is free (plus ~$6–12/month server cost). n8n Cloud starts at $20/month for 2,500 executions. Make starts at $9/month for 10,000 operations. For low-volume cloud use, Make is cheaper. For high-volume use, self-hosted n8n on a VPS beats Make at any scale.
n8n has improved a lot for non-technical users with better templates and a cleaner canvas. But self-hosted setup still requires technical confidence. If you have zero technical background, Make is the friendlier starting point — you can always migrate later.
Agencies with technical capacity should strongly consider self-hosted n8n — unlimited executions with no per-workflow SaaS fees make it dramatically more cost-effective at scale. Agencies without server management experience are better served by Make's Teams plan.
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