n8n vs Make: The 2026 Definitive Comparison for Workflow Automation | NoCodeRank

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🏆 Quick Verdict

Choose n8n if: You have a technically proficient team (DevOps, JavaScript, API knowledge) and prioritize strong control over your data, infrastructure, and logic. Its open-source, self-hosted option is ideal for high-volume, complex workflows (especially AI-driven ones) where predictable, long-term costs and deep customization matter more than convenience. Be prepared for meaningful operational overhead.

Choose Make if: You need a user-friendly, cloud-based platform to ship automations quickly without managing servers. It’s ideal for business users, SMBs, and teams that value ease of use and a vast library of native integrations over low-level control. You’ll need to actively monitor its per‑operation pricing, as costs can escalate with complex, high-volume scenarios.

What is n8n?

n8n is a powerful, open-source workflow automation platform built on a "fair-code" model. Its core philosophy centers on giving developers and technical teams maximum control, customization, and data sovereignty. Unlike purely visual tools, n8n is designed as an engineer's workbench, combining a node-based visual editor with the ability to inject custom JavaScript, Python, and direct API calls. This makes it well-suited for bespoke integrations and complex logic chains that go beyond pre-built modules.

The platform shines in its deployment flexibility. You can self-host n8n for free on your own infrastructure, keeping all data in-house, or use its managed cloud service for a balance of control and convenience. This makes it a strong choice for organizations with stringent compliance needs, teams running high-volume automations where cloud costs could balloon, or anyone who needs to connect to niche or proprietary systems that lack standard connectors.

💡 Did You Know? The name "n8n" is a numeronym for "nodemation" (node-based automation). Its open-source roots mean a global community has built over 2,900 community-contributed nodes, extending its core capabilities far beyond its official integrations.

Key Features of n8n

Fair-Code Licensing: Self-host the full-featured source code for free, forever.
Code & API-First Design: Execute custom JavaScript/Python code in any node and connect to any API via HTTP requests.
Advanced AI Workflow Capabilities: Native nodes for OpenAI, Anthropic, Hugging Face, and local LLMs via Ollama, with support for RAG (Retrieval-Augmented Generation) and LangChain.
Flexible Deployment: Choose between self-hosting (Docker, npm) or a managed cloud service (n8n.cloud).
High-Volume Cost Efficiency: Cloud pricing is per workflow execution, not per operation, making complex multi-step automations cost-effective at scale.
Enterprise-Grade Security (Self-Hosted): Full control over data residency, encryption, and access when self-hosting.
Extensible Node Library: Over 1,200 official integrations, supplemented by thousands of community-built nodes.

What is Make?

Make (formerly Integromat) is a fully managed, cloud-native automation platform built for accessibility and speed. Its design philosophy prioritizes ease of use, visual simplicity, and rapid deployment, making it a favorite among business users, marketers, and operations teams in SMBs. Make abstracts away most of the underlying complexity of APIs and infrastructure, offering a highly intuitive drag-and-drop interface where automations are built as visual "scenarios."

The platform excels at connecting popular SaaS applications quickly, thanks to one of the largest libraries of pre-built, native integrations. Users can prototype and deploy workflows in minutes without writing a line of code. The trade-off is its consumption-based pricing model: each step (or "operation") in an automation costs credits. This model requires careful planning, as the cost of complex, high-volume automations can grow unexpectedly.

Key Features of Make

Intuitive Visual Builder: Drag-and-drop, mind-map-style interface that’s approachable for non-technical users.
Vast Native Integration Library: Over 3,100 pre-built app modules for plug-and-play connectivity.
Managed Cloud Service: No infrastructure to manage; Make handles scaling, uptime, and security.
Accessible AI Tools: AI Assistant for building scenarios, pre-built AI app modules (OpenAI, etc.), and Model Context Protocol (MCP) for AI agents.
Comprehensive Templates: Thousands of pre-made scenario templates for common use cases.
Enterprise Security & Compliance: SOC 2 Type II, GDPR, and ISO 27001 certifications for the cloud platform.
Data Storage and Tools: Built-in data stores, functions, and tools for basic data manipulation without code.

Feature Comparison: n8n vs Make

This head-to-head breakdown goes beyond feature lists to examine how each platform's design philosophy impacts real-world use, scalability, and total cost.

Ease of Use

Winner: Make

For sheer accessibility, Make is the clear winner. Its visual editor is significantly more intuitive for beginners. You can drag modules onto a canvas, connect them with lines, and see data flow in a way that makes logical sense without technical knowledge. Building a simple automation between two common apps like Google Sheets and Slack can be done in under 10 minutes.

n8n’s interface is clean and powerful but presents a steeper learning curve. While it’s also visual, understanding how to configure nodes requires comfort with JSON data structures, HTTP methods, and often, basic JavaScript for transformations. Debugging a complex, branching workflow in n8n is a more technical process. For a non-developer, Make’s path from idea to working automation is noticeably faster and smoother.

Integrations & Connections

Winner: Tie (for different reasons)

Make wins on breadth and convenience. With over 3,100 native integrations, you’re more likely to find a pre-built, optimized module for your favorite SaaS tool. These modules often have multiple pre-configured triggers and actions, simplifying setup.

n8n wins on depth and flexibility. While it has “only” ~1,200 official integrations, its true power is the ability to connect to anything with an API. Using the HTTP Request node or writing a custom node, you can integrate with proprietary internal systems or niche services Make doesn't support. The ~2,900 community nodes further close the gap, offering specialized functionality. If you need a deep, customized connection, n8n is typically superior.

AI Capabilities

Winner: n8n

For sophisticated, cost-optimized AI workflows, n8n is stronger. It provides direct nodes for all major AI providers (OpenAI, Anthropic, Google AI) and, critically, supports running local LLMs via Ollama. This allows for sandboxed, private, and extremely cost-effective AI processing. You can build complex RAG pipelines with vector databases and implement multi-agent systems using frameworks like LangChain, all with granular control over logic and error handling.

Make excels at making AI accessible. Its AI Assistant can generate scenarios from a description, and its pre-built AI modules let business users easily add AI steps. However, this ease can lead to escalating costs, as each AI call consumes operations. For high-volume or highly customized AI tasks, Make’s pricing model can become prohibitive, whereas n8n’s self-hosted or per-execution model usually offers better cost predictability.

Pricing and Economic Scalability

Winner: n8n (for predictable scaling)

This is a critical differentiator. Make uses a per-operation pricing model. Every module in a scenario (a filter, a router, an action) consumes operations. A complex workflow with loops and high data volume can consume tens of thousands of operations daily, leading to unpredictable bills and potential “cost shock.”

n8n uses a per-execution model in its cloud plan. You are charged once for a complete run of a workflow, regardless of how many steps or data transformations it contains. For intricate, multi-step automations, this is often more economical at scale. Its self-hosted option has zero licensing cost, though you must factor in infrastructure and DevOps labor. For organizations with the technical ability to self-host, n8n can provide very predictable long-term economics.

To make this concrete: small teams often start with a single VPS (for example, a mid-range cloud instance plus a managed database) and grow into more robust setups with monitoring, backups, and staging environments as automation volume increases. That progression is where the real cost of self-hosting lives.

Performance & Reliability

Winner: n8n (for self-hosted control)

Make’s performance is tied to its cloud service. It offers high uptime (99.9% SLA on Pro plans) and handles scaling automatically. You trade control for convenience; if Make has an outage, your automations stop, and you’re bound by their status page and SLAs.

n8n’s performance is ultimately what you design. When self-hosted, you control the server specs, database, and network, allowing you to build a resilient, scalable architecture tailored to your needs. You can run it on-premises for ultra-low latency or in a region of your choice. This puts the burden of reliability and hardening on your team but gives you the ability to create stricter uptime guarantees and tune performance for your exact workloads.

Pricing Comparison (February 2026)

n8n Starter

$49per month (cloud)

300 workflow executions/month
Unlimited team members
7-day execution log retention
Community support

Try n8n Cloud

Make Free

$0forever free

1,000 operations/month
2 active scenarios
Check data updates every 15 min
Community support

Try Make Free

Detailed Comparison Table

Feature	n8n	Make
Core Philosophy	Open-source, developer-centric control	Cloud-based, business-user convenience
Primary Hosting	Self-hosted or Managed Cloud	Fully Managed Cloud Only
Learning Curve	Steep (requires tech skills)	Gentle (visual, drag-and-drop)
Pricing Model	Per execution (cloud) or free (self-hosted)	Per operation (consumption-based)
Native Integrations	~1,200 official	~3,100+
Custom Code	JavaScript, Python nodes	Limited functions
AI & LLM Support	Deep customization, local LLMs	Pre-built modules, AI Assistant
Data Sovereignty	Full control when self-hosted	Managed by vendor
Enterprise Security	Your responsibility (self-hosted)	SOC 2, ISO 27001 certified
Best For	Developers, high-volume/complex workflows, compliance	Business teams, SMBs, rapid prototyping, common SaaS stacks

n8n Pros and Cons

Pros

High control & flexibility: Self-host for full data sovereignty and customize every aspect with code.
Predictable scaling costs: Per-execution cloud pricing or free self-hosting can make high-volume automation economically viable.
Deep AI/ML capabilities: Build sophisticated, cost-optimized AI agents, RAG systems, and run local LLMs.
Connect to almost anything: HTTP Request node and custom node SDK let you integrate with any API, internal or external.
Strong developer appeal: Code-friendly design, Git version control compatibility, and CLI tools.
Active open-source community: Access to thousands of free, community-built nodes and templates.

Cons

Steep learning curve: Requires knowledge of APIs, JSON, and often JavaScript to use effectively.
Operational overhead: Self-hosting demands ongoing DevOps resources for setup, security, and maintenance.
Less intuitive UI for non-technical users: The node-based editor is powerful but less immediately accessible than Make's visual canvas.
Fewer "plug-and-play" integrations: While extensible, it has fewer pre-packaged, optimized native connectors than Make.
Security is your burden: You are responsible for patching vulnerabilities and securing your self-hosted instance.

Make Pros and Cons

Pros

Superior ease of use: One of the most intuitive visual builders on the market, ideal for citizen developers.
Vast native integration library: Over 3,100 pre-built apps with multiple triggers/actions for rapid setup.
Zero infrastructure management: A fully managed service—no servers, scaling, or updates to worry about.
Rapid prototyping & deployment: Go from idea to live automation in minutes using templates and drag-and-drop.
Built-in enterprise security: Benefit from Make's SOC 2, GDPR, and ISO compliance without extra work.
Helpful AI features: AI Assistant for building scenarios and easy-to-add AI module steps.

Cons

Unpredictable, high potential costs: Per-operation pricing can lead to bill shock with complex or high-volume workflows.
Limited customization: You're confined to the logic of pre-built modules; complex data transformations can be cumbersome.
Vendor lock-in & data control: Your automations and data reside entirely on Make's cloud.
Visual complexity at scale: Complex scenarios can become a tangled web of routes and filters, hard to debug and maintain.
Not ideal for bespoke systems: Integrating with proprietary/internal APIs is generally more difficult than with n8n.

Use Case Scenarios

Best for n8n

Building a Custom AI Customer Support Agent: Combining a vector database (for RAG), multiple LLM calls (OpenAI + local model for cost), and internal API calls to fetch customer data.
High-Volume E-commerce Data Synchronization: Self-hosting to process thousands of orders daily between a custom ERP, Shopify, and a warehouse system with complex, multi-step logic per order.
Financial/Healthcare Compliance Automation: Where data must never leave your infrastructure, requiring a self-hosted, auditable automation platform with custom encryption steps.
Developing Internal Tooling Integrations: Connecting niche, proprietary, or legacy internal systems that lack standard SaaS connectors via custom-built nodes.
Cost-Optimized Social Media Content Pipeline: Automating image generation (via AI), scheduling, cross-posting, and analytics across multiple platforms where per-operation costs on other platforms would be prohibitive.

Best for Make

Marketing Lead Nurturing Workflow: Easily capturing form leads (Typeform), adding them to a CRM (HubSpot), sending a welcome email (Mailchimp), and creating a task in a project tool (ClickUp).
Social Media Listening & Alerting: Monitoring brand mentions on Twitter/X or Reddit and posting formatted alerts to a Slack channel for the team.
Quick SaaS App Synchronization: Keeping user lists in sync between a community platform (Circle) and an email marketing tool (ConvertKit) with simple filter logic.
Business User Reporting Automation: A sales ops manager pulling daily deal data from Salesforce, formatting it in Google Sheets, and emailing a PDF report via Gmail—all without involving IT.
Rapid Prototyping for Process Proof-of-Concept: Testing if an automation idea works by building a functional scenario in an afternoon before committing developer resources to a more robust build.

Which Should You Choose?

The decision between n8n and Make isn't about which tool is objectively better, but which philosophy aligns with your organization's capabilities and goals. Ask yourself these questions:

Choose n8n if:

You have in-house developers or a strong DevOps team comfortable with servers and code.
Data sovereignty, security control, and compliance (GDPR, HIPAA) are critical requirements.
You run high-volume automations where Make's per-operation costs would be unpredictable and high.
You need to integrate with custom, proprietary, or legacy internal systems.
You are building advanced, multi-step AI workflows where cost optimization and customization are key.

Choose Make if:

Your primary users are business analysts, marketers, or ops managers with little to no coding skill.
You want to deploy automations in hours or days, not weeks, with minimal setup.
Your stack consists mainly of popular SaaS apps (Salesforce, Slack, Google Workspace, etc.).
You prefer a predictable monthly subscription and can manage/optimize operation usage carefully.
You lack the IT resources or desire to manage servers, security patches, and software updates.

Frequently Asked Questions

Winner: It depends (n8n for technical teams, Make for business teams)

Our Recommendation

There is no single “best” platform in the n8n vs Make debate. The winner is the one that matches your organization's DNA.

For Technical Teams & Scalable Enterprises: n8n is often the better long-term choice. If you have the technical resources, its combination of control, cost-effective scaling (especially for self-hosting), and extensive customization can future-proof your automation investment. It's the tool that grows with you into complex AI and system integration territory.

Try n8n Free →

For Business Teams & Agile SMBs: Make is an excellent starting point. Its ease of use lowers the barrier to automation, allowing you to solve real business problems quickly. Just be vigilant about monitoring operation consumption as your automations grow in complexity and volume to avoid cost surprises, and revisit your platform choice if you outgrow its economics or flexibility.

Try Make Free