Make vs n8n for Teams in 2026: Which One Actually Wins?
You've outgrown Zapier. Your team is running dozens of automations, hitting operation limits, and your monthly bill has crept into uncomfortable territory. Make and n8n are the two names that keep coming up โ and choosing the wrong one will cost you either money, time, or both.
This isn't a surface-level features list. This is a direct, use-case-driven breakdown of where each tool wins, where it falls flat, and which team profile should choose which platform in 2026.
What's Actually Changed in 2026
Both platforms have matured significantly. Make (formerly Integromat) has doubled down on its visual scenario builder and expanded its AI-step integrations, making it easier for ops teams to connect tools without writing a line of code. n8n has pushed hard on its AI agent capabilities, native LLM nodes, and a significantly improved cloud offering โ while keeping its self-hosted model as a core differentiator.
The gap between them has narrowed on features, but widened on philosophy. Make is a polished SaaS product. n8n is a power tool with an open-source soul. That distinction matters more than any individual feature.
Interface and Ease of Use
Make's visual canvas is genuinely excellent. Modules snap together cleanly, the data mapping is intuitive, and debugging is straightforward even for people who've never written a workflow before. If your team includes marketers, ops coordinators, or project managers who need to build and maintain automations themselves, Make's interface removes most of the friction.
n8n's interface has improved โ the node editor is cleaner than it was two years ago โ but it still assumes you're comfortable thinking in logic flows. Concepts like expressions, function nodes, and credential scopes require a bit of ramp-up. For a team with even one technically-minded member, this isn't a dealbreaker. For an all-business team, it creates a bottleneck.
Verdict: Make wins for non-technical teams. n8n wins once you have someone comfortable with logic and light code.
Pricing: Where the Real Difference Lives
This is where the conversation often ends for growing teams.
| Feature | Make (Team Plan) | n8n Cloud (Pro) | n8n Self-Hosted |
|---|---|---|---|
| Monthly Cost | ~$29/mo (10k ops) | ~$50/mo (10k executions) | ~$5โ15/mo (server) |
| Operations Model | Per-operation billing | Per-execution billing | Unlimited |
| Users Included | 3 users | 5 users | Unlimited |
| Custom Code | Limited | Full JS/Python nodes | Full JS/Python nodes |
| Data Privacy | Cloud only | Cloud + EU region | Full control |
| Free Tier | 1,000 ops/month | 2,500 executions/month | Fully free |
Make's per-operation model punishes complex workflows. A single scenario that passes data through six modules counts as six operations. At scale, this adds up fast. n8n charges per execution regardless of step count โ a model that significantly favors complex, multi-step automations.
For teams running high-volume, multi-step workflows, n8n's pricing model is often 3โ5x cheaper at equivalent workload.
Integration Depth and Reliability
Make has over 1,500 native app integrations. That breadth is real, and for standard business tools โ Google Workspace, Slack, HubSpot, Notion, Airtable โ Make's connectors are polished and reliable. The built-in error handling and retry logic is solid without requiring custom configuration.
n8n has fewer native integrations out of the box (around 400 official nodes), but its HTTP Request node and community node library close most of that gap. If your stack includes common SaaS tools, n8n will cover 90% of your needs. If you're automating niche or industry-specific software, Make may have the connector already built.
One area where n8n has clearly pulled ahead: AI integrations. Native nodes for OpenAI, Anthropic, Gemini, and local LLMs like Ollama make n8n a strong choice for teams building AI-assisted workflows โ summarizing emails, routing support tickets, generating content, or triaging data with language models baked directly into the automation.
Control, Privacy, and Security
This is n8n's strongest argument for teams in regulated industries or privacy-conscious organizations.
Self-hosted n8n means your data never leaves your infrastructure. Workflow logic, credentials, execution logs โ all of it stays on your server. For healthcare, legal, fintech, or any company with strict data residency requirements, this is often non-negotiable.
Make is cloud-only. It offers solid security certifications (SOC 2, GDPR compliance), but you're trusting their infrastructure. For most teams, this is fine. For teams handling sensitive customer data or subject to compliance audits, n8n's self-hosted model eliminates a category of risk entirely.
Which Team Should Choose Which Tool
Choose Make if:
- Your team is primarily non-technical and needs fast setup
- You're connecting common SaaS tools without heavy customization
- You want 24/7 support without managing infrastructure
- You're running under 50,000 operations per month
Choose n8n if:
- You have at least one developer or technical ops person on the team
- You're running high-volume or complex multi-step workflows
- Data privacy or self-hosting is a requirement
- You're building AI-augmented automations with LLM nodes
- You want predictable pricing that doesn't scale with complexity
The Bottom Line
Make and n8n aren't competing for the same customer anymore. Make is the right tool for teams that want automation to feel like a product โ polished, supported, and ready out of the box. n8n is the right tool for teams that want automation to feel like infrastructure โ flexible, private, and cost-effective at scale.
If you're a 5-person startup with mixed technical skills and standard tooling, start with Make. If you're a 20-person company with a developer on staff, compliance requirements, or a growing automation bill, the migration to n8n will pay for itself within months.
Either way, the days of tolerating Zapier's pricing at scale are over. Both of these platforms offer more power for less money โ you just need to pick the right one for how your team actually works.