n8n vs Make (2026): Complete Comparison Guide

n8n vs Make: Quick Comparison

Before we get into the details, here is a high-level overview of how these platforms stack up:

What Is n8n?

n8n (pronounced "n-eight-n") is an open-source workflow automation platform launched in 2019.

It uses a "fair-code" model, meaning the source code is publicly available, but commercial use requires a license for certain features.

The platform is built for technical users who want full control over their automation infrastructure. Its defining feature is the ability to self-host: you can run n8n on your own servers, giving you complete ownership of your data and no limits on workflow executions.

n8n uses a node-based visual builder where you connect different nodes (representing apps, logic, or transformations) to create workflows. Each workflow can contain unlimited steps, and you can add custom JavaScript or Python code when pre-built nodes do not cover your use case.

Key characteristics of n8n:

• Open source foundation. The core platform is open source, with a vibrant community contributing integrations and improvements.

• Self-hosting as default. Most n8n users run it on their own infrastructure, though cloud hosting is available.

• Developer-friendly. Code nodes, API access, and webhooks give developers full flexibility.

• Execution-based billing. Cloud plans charge per workflow execution, not per step.

What Is Make?

Make (formerly Integromat) is a cloud-based visual automation platform founded in Prague in 2012. It rebranded from Integromat to Make in 2022 after Celonis acquired it.

It's designed for accessibility. Its visual "scenario" builder is more polished and approachable than most automation tools, making it popular with marketing teams, operations managers, and non-technical users who need to automate without developer support.

The platform runs entirely in the cloud. There is no self-hosting option. All workflows execute on Make's servers (located in Frankfurt, Germany), and billing is based on operations, which are the individual steps your workflows perform.

Key characteristics of Make:

• Visual-first design. The module-based builder is intuitive and well-documented.

• Extensive integrations. Over 2,000 pre-built connectors for popular apps and services.

• Cloud-only. Fully managed infrastructure with no self-hosting option.

• Operation-based billing. Plans charge per operation (each step counts separately).

Pricing Comparison: The Full Breakdown

Pricing is where n8n and Make diverge most. Understanding the billing models is critical for estimating your actual costs.

n8n Pricing Model: Executions

n8n charges per workflow execution. One execution equals one complete run of your workflow, regardless of how many steps it contains. A workflow with 5 steps and a workflow with 50 steps both count as one execution when they run once.

This model rewards complex workflows. You can build sophisticated, multi-step automations without worrying about each step adding to your bill.

n8n Cloud Plans:

Self-Hosted n8n:

The Community Edition is completely free with unlimited executions. You pay only for your server infrastructure, which typically costs $50-200/month for a production-ready setup on AWS, DigitalOcean, or similar providers.

For teams with DevOps capability, self-hosting eliminates usage-based fees entirely. A $100/month server can handle workflows that would cost thousands on cloud plans.

Make Pricing Model: Operations

Make charges per credit. Every action a module performs counts as one credit. A workflow with 5 steps that runs once uses 5 credits. The same workflow running 100 times uses 500 credits.

This model is simple to understand but can become expensive for complex or high-frequency workflows. Polling triggers (checking for new data at intervals) also consume credits, which catches some users off guard.

Make Cloud Plans:

Cost at Scale: Real-World Examples

Let us compare actual costs for common automation scenarios.

Scenario 1: Simple CRM sync

A workflow that syncs new contacts from a form to your CRM. It has 3 steps and runs 50 times per day.

• n8n: 50 executions/day = 1,500/month. Covered by Starter plan ($20/month).

• Make: 150 operations/day = 4,500/month. Covered by Core plan ($9/month).

Winner: Make (cheaper for simple, low-volume workflows).

Scenario 2: Complex lead processing

A workflow that enriches leads, scores them, routes to different CRMs, and sends Slack notifications. It has 15 steps and runs 200 times per day.

• n8n: 200 executions/day = 6,000/month. Covered by Pro plan ($50/month).

• Make: 3,000 credits/day = 90,000/month. Requires purchasing additional credits beyond Teams plan. Estimated cost: $300+/month.

Winner: n8n (significantly cheaper for complex workflows).

Scenario 3: High-frequency data sync

A workflow that checks for new records every minute and processes batches. It has 10 steps and runs 1,440 times per day (once per minute).

• n8n (self-hosted): 43,200 executions/month. $0 usage cost (only infrastructure ~$100/month).

• Make: 432,000 operations/month. Would cost hundreds or thousands depending on plan tier.

Winner: n8n self-hosted (no comparison for high-volume).

Self-Hosting: The Defining Difference

This is the biggest technical difference between n8n and Make. It is often the deciding factor for teams with specific requirements.

n8n: Full Self-Hosting Support

n8n can be deployed on your own infrastructure. You can run it on AWS, Google Cloud, Azure, DigitalOcean, your own data center, or even a Raspberry Pi for testing.

Self-hosting gives you:

• Complete data ownership. Workflow data, credentials, and execution logs stay on your servers.

• No execution limits. The Community Edition has no caps. Run as many workflows as your hardware can handle.

• Compliance control. Essential for industries with data residency requirements (healthcare, finance, government).

• Cost predictability. Pay for infrastructure, not usage. A $100/month server replaces thousands in cloud fees for high-volume teams.

• Customization freedom. Modify the source code, add custom nodes, integrate with internal systems.

The trade-off is responsibility. You manage updates, security patches, backups, and scaling. Teams without DevOps capability may find this burdensome.

Make: Cloud-Only

Make has no self-hosting option. Every workflow runs on Make's servers in Frankfurt, Germany.

For many teams, this is fine. You get:

• Zero infrastructure management. No servers to maintain, no updates to apply.

• Guaranteed uptime. Make handles scaling and reliability.

• Faster onboarding. Sign up and start building immediately.

But for teams with strict data policies, cloud-only is a non-starter. If your company requires data to stay within your own infrastructure, Make is not an option.

Integrations and Connectors

Both platforms let you connect to external apps and services, but they approach integrations differently.

Make: Breadth of Native Integrations

Make offers over 2,000 pre-built integrations, covering most popular SaaS tools out of the box. If you use mainstream apps like HubSpot, Salesforce, Google Workspace, Slack, or Shopify, Make likely has a native connector.

Make also supports custom API requests (HTTP modules) for services without native integrations, but the strength is the breadth of ready-made options.

n8n: Depth and Flexibility

n8n has around 400 native integrations, fewer than Make but covering most common tools. Where n8n excels is in customization.

The HTTP Request node is extremely flexible, supporting any REST API with full control over headers, authentication, and request structure. The Code nodes (JavaScript and Python) let you write custom logic for transformations that no pre-built integration could handle.

The open-source community also contributes integrations, so the library grows continuously.

Bottom line: If you need plug-and-play connectors for niche apps, Make has an edge. If you are comfortable with APIs and custom code, n8n's flexibility makes up for fewer native integrations.

AI Features and Capabilities

Both platforms have invested heavily in AI capabilities, recognizing that automation increasingly involves AI-powered transformations.

n8n AI Features

n8n has embraced AI as a core feature set:

• AI nodes. Native nodes for OpenAI, Anthropic (Claude), Google AI, and other LLM providers.

• LangChain integration. Built-in support for LangChain, enabling complex AI agent workflows.

• Vector database connectors. Integrations with Pinecone, Qdrant, and other vector stores for RAG applications.

• AI agent templates. Pre-built templates for common AI use cases like document processing and chatbots.

n8n's AI capabilities are particularly strong for developers building custom AI applications. You can chain multiple AI operations, implement retrieval-augmented generation (RAG), and build sophisticated AI agents.

Make AI Features

Make has introduced AI-specific features:

• Make AI Agents. No-code AI agents that can perform tasks across your connected apps.

• Make AI Toolkit. Tools for text generation, summarization, and data extraction.

• OpenAI integration. Native connector for GPT models.

• Custom AI provider connections. As of late 2025, all paid plans can connect their own OpenAI, Anthropic, or other API keys.

Make's AI features are more accessible to non-technical users but less flexible for custom AI development.

Learning Curve and User Experience

The platforms target different user profiles, and this shows in their interfaces. At Goodspeed, we're also always happy to help you know what to choose.

Make: More Accessible

Make's interface is polished and intuitive. New users can often build their first working automation within an hour. The visual builder uses a clear left-to-right flow, and the documentation is comprehensive.

Make also provides extensive templates for common use cases, reducing the need to build from scratch.

That said, Make has its own learning curve for advanced features. Routers, iterators, and error handlers require understanding, and the operation-based billing model can be confusing at first.

n8n: Steeper but Rewarding

n8n is more complex to learn, especially if you are self-hosting. The interface is functional but less polished than Make. Setting up your first workflow takes longer, and concepts like credentials management and execution modes require more initial effort.

However, once you understand n8n, you have far more power. The ability to write custom code, the flexibility of the HTTP Request node, and the control from self-hosting make n8n capable of automations that would be difficult or impossible in Make.

Recommendation: Non-technical users and teams without developer support will find Make easier. Technical teams and developers will appreciate n8n's flexibility once past the initial learning curve.

Error Handling and Reliability

Automations fail. APIs return errors, data is malformed, services go down. How each platform handles failures matters for production reliability.

Make Error Handling

Make has sophisticated error handling built into the visual builder:

• Error handlers. Define specific actions when a module fails (retry, ignore, send alert).

• Break and resume. Failed scenarios can be paused and resumed after fixing the issue.

• Incomplete executions. A dedicated queue shows failed runs for debugging.

n8n Error Handling

n8n also provides robust error handling:

• Error workflows. Trigger separate workflows when main workflows fail.

• Retry on failure. Configure automatic retries with backoff.

• Continue on fail. Individual nodes can be set to continue even if they error.

• Execution logs. Detailed logs for debugging failed runs.

Both platforms handle errors well. Make's visual error handling is slightly more intuitive; n8n's error workflows are more flexible for complex recovery logic.

When to Choose n8n

n8n is the better choice if:

• You need self-hosting. Data sovereignty, compliance requirements, or internal security policies mandate keeping data on your own infrastructure.

• You run high-volume automations. The execution-based model (or unlimited self-hosted) is dramatically more cost-effective at scale.

• Your team is technical. Developers and technical operators will appreciate n8n's flexibility, code nodes, and API access.

• You want to avoid vendor lock-in. Self-hosting means you control your automation infrastructure and can migrate or modify freely.

• You are building AI applications. LangChain integration and AI nodes make n8n powerful for custom AI workflows.

• You need complex custom logic. Code nodes support JavaScript and Python for transformations beyond what pre-built modules can do.

If you’ve decided n8n is the right platform, execution matters. Work with us at Goodspeed, a specialist n8n agency that builds production-ready automation systems.

When to Choose Make

Make is the better choice if:

• You need extensive native integrations. Make's 2,000+ connectors mean less time building custom integrations.

• Your team is less technical. Marketing, operations, and business teams find Make more approachable.

• You want managed infrastructure. No servers to maintain, no updates to manage, no scaling to worry about.

• You have predictable, moderate volume. Make is cost-effective for teams with steady, lower-volume automation needs.

• You value polish and templates. Make's interface and pre-built templates accelerate time to first workflow.

• You need team collaboration features. Make's Teams plan offers shared scenarios and team management out of the box.

Migration Considerations

If you are currently using Make and considering n8n, or vice versa, here is what to expect.

Migrating from Make to n8n:

Workflows cannot be automatically imported. You will need to rebuild them in n8n. The logic translates, but the visual structure differs. Plan for 2-4 hours per workflow for simple automations, longer for complex scenarios. Benefits include lower costs at scale, self-hosting control, and no vendor lock-in.

Migrating from n8n to Make:

Similar rebuild process required. Make's visual interface may accelerate rebuilding for simpler workflows. Consider migration if you need Make's broader integration library or prefer fully managed infrastructure. Be prepared for higher costs at volume.

Hybrid approach:

Some teams run both platforms. Use Make for marketing and operations workflows where ease of use matters. Use n8n for complex, high-volume, or data-sensitive automations. This avoids forcing every use case into one platform.

Why Goodspeed Builds with n8n

At Goodspeed, we specialize in n8n for client automation projects. After working with both platforms across dozens of engagements, here is why we recommend n8n for our clients:

Reliability at scale. n8n's architecture handles high-volume, complex workflows without the cost escalation inherent in operation-based pricing. For clients running thousands of executions daily, n8n is dramatically more economical.

Client data ownership. Many of our clients have data residency requirements or internal policies that prohibit sending data to third-party cloud providers. Self-hosted n8n keeps automation infrastructure fully in-house.

Long-term cost control. Self-hosting eliminates per-execution fees. Clients pay predictable infrastructure costs, not variable usage fees that grow with success.

Flexibility for complex use cases. Code nodes and full API access let us build automations that would be impossible in more constrained platforms. When a client needs custom logic, we can implement it.

Future-proofing. Self-hosted, open-source infrastructure means clients are not locked into a single vendor. If needs change, they have options.

That said, we are not dogmatic about tooling. Make is solid for the right use case. If your needs are better served by Make, particularly for non-technical teams or simpler workflows, we will tell you. See how we implement n8n for operations teams.