Skip to content
aicoolies logo

n8n vs Make — Self-Hosted Open-Source vs Cloud Visual Automation

n8n and Make both offer visual workflow builders with strong data transformation capabilities, but differ fundamentally in deployment model and pricing. n8n is open-source with free self-hosting and execution-based pricing. Make is cloud-only with operation-based pricing and the most polished visual builder in the market. This comparison helps technical teams decide between infrastructure control and managed convenience.

analyzed by Raşit Akyol April 1, 2026 updated September 5, 2026

n8n reviewMake review

Verdict

n8n captures the win by offering complete data privacy through self-hosting, custom JavaScript/Python execution within workflows, and cutting-edge LangChain-powered AI agent nodes. Unlike Make's usage-tiered pricing that penalizes high-volume data polling, n8n allows unlimited executions on your own infrastructure or transparent cloud plans. For developers building complex integrations and AI-driven automation, n8n provides superior control and cost efficiency. Our pick: n8n.


Quick Comparison

n8nwinner

Pricing
n8n offers a free self-hosted Community Edition with unlimited workflows. Managed n8n Cloud plans start at $24/month (€24/mo, or €20/mo billed annually) for Starter (2,500 executions/month), $60/month for Pro (10,000 executions/month), and custom pricing for Enterprise.
Pricing Model
Freemium
Platforms
Web, Self-hosted (Docker, npm)
Open Source
No
Telemetry
Clean
Status
Active
Editorial Pick
—
Last Verified
Aug 26, 2026
Description
n8n is a source-available workflow automation platform for connecting apps, APIs, data, and AI models through visual workflows and code. It supports self-hosted deployments and n8n Cloud, with integrations across communication, databases, CRM, project management, and model providers. Teams can combine deterministic automation with AI-powered steps and agent workflows while retaining control over deployment and data.

Make

Pricing
Freemium visual workflow automation and iPaaS integration platform by Celonis. Free tier ($0/mo) includes 1,000 credits/operations per month, 2 active scenarios, and a 15-minute execution interval. Core plan starts at $9/mo billed annually ($10.59/mo billed monthly) for 10,000 credits/operations with unlimited active scenarios, 1-minute scheduling, and Make API access. Pro plan starts at $16/mo billed annually ($18.82/mo billed monthly) adding custom variables, priority execution, and full-text execution log search. Teams plan starts at $29/mo billed annually ($34.12/mo billed monthly) introducing multi-user team roles, granular permissions, and shared scenario templates. Enterprise plan provides custom tiered pricing with high-volume credit bundles, SAML 2.0 SSO, SCIM user provisioning, audit logs, 24/7 enterprise SLA, and HIPAA/SOC 2 compliance.
Pricing Model
Freemium
Platforms
Web-based; API, webhooks, custom apps, and integrations with thousands of apps
Open Source
No
Telemetry
Clean
Status
Active
Editorial Pick
—
Last Verified
Sep 6, 2026
Description
Visual workflow automation platform formerly known as Integromat, built around a drag-and-drop canvas for complex multi-step workflows. Features routers for conditional branching, iterators for array processing, aggregators, webhooks, and HTTP modules for custom API calls. Best suited to power users and technical teams that need granular data transformation and workflow logic rather than only simple trigger-action automations.

What Sets Them Apart

When automation needs outgrow Zapier's linear model, teams typically evaluate n8n and Make as their next platform. Both offer node-based visual builders with branching, loops, and error handling — but they represent different trade-offs between control and convenience. n8n gives you the source code, self-hosting freedom, and unlimited customization. Make gives you a polished cloud experience with the most intuitive visual workflow designer available.

n8n and Make at a Glance

The deployment model is the fundamental differentiator. n8n can run anywhere — a $5/month VPS, your company's Kubernetes cluster, a Raspberry Pi, or n8n Cloud if you prefer managed hosting. This flexibility matters for data sovereignty, compliance, and air-gapped environments. Make is exclusively cloud-hosted, with data processed on their infrastructure. For teams bound by GDPR, HIPAA, or internal data governance policies, n8n's self-hosting capability is often the deciding factor.

Pricing mechanics favor n8n for high-volume use cases. n8n's self-hosted Community Edition is completely free with no limits on executions, workflows, or users. n8n Cloud starts at €20/month for 2,500 executions. Make's free tier includes 1,000 operations/month, with paid plans starting at $9/month for 10,000 operations. The key distinction: n8n counts one execution per workflow run regardless of steps, while Make counts each module operation separately. A 10-step workflow running 1,000 times costs 1,000 executions on n8n but 10,000 operations on Make.

Make's visual builder leads the industry in design quality. Workflows render as clean flowcharts with clear data flow visualization, collapsible modules, and an intuitive routing interface that makes complex automations readable. n8n's canvas-based builder is powerful and improving rapidly, but its interface exposes more technical detail — JSON structures, expression editors, and debugging panels that feel more like a development tool than a design tool. Developers appreciate this depth; non-technical users may find it intimidating.

Self-Hosting, Visual Builder, and AI Nodes

Custom code and extensibility give n8n a clear advantage for technical teams. n8n's Code node supports JavaScript and Python execution within workflows, and developers can build custom nodes as npm packages. The entire platform is extendable through its open architecture. Make offers a Code module for JavaScript/Python and a custom app builder, but the customization is bounded by the platform's cloud constraints — you cannot modify the runtime environment or add system-level dependencies.

AI and agent capabilities represent n8n's most significant recent advancement. n8n includes a native AI agent builder with LLM nodes, tool calling, memory management, and vector store integrations. You can build autonomous agents that reason, use tools, and chain multi-step AI operations within your automation workflows. Make provides AI modules for calling external APIs (OpenAI, Anthropic) and basic prompt-based operations, but lacks the agent orchestration architecture that n8n offers natively.

Integration ecosystems differ in size but converge on popular tools. Make offers approximately 2,000 pre-built app integrations with one of the better custom app builder experiences for creating your own connectors. n8n has 1,000+ native nodes supplemented by thousands of community-built nodes available through its node marketplace. Both platforms support HTTP/webhook connections to any API, so the native integration count matters less for technically capable teams.

Pricing and Integration Depth

Error handling approaches reflect each platform's technical depth. Make provides per-module error handlers, break/resume flows, retry configurations, and dedicated error routes — all configured through the visual interface. n8n offers workflow-level error handling with a dedicated Error Trigger node, per-node retry settings, and the ability to inspect and replay individual executions with their original data. For debugging complex failures, n8n's execution replay capability is particularly valuable.

Community and ecosystem are different in character. Make has a large community of business automation enthusiasts with extensive template libraries and an active community forum. n8n has a passionate open-source community of developers who contribute custom nodes, share advanced patterns, and provide support through Discord. n8n's community tends to produce more technically sophisticated content, while Make's community excels at business process automation patterns.

The Bottom Line


FAQ

How do n8n and Make differ in their deployment architecture, data privacy, and execution environments?

n8n is a source-available, self-hostable workflow automation engine built with Node.js and TypeScript running locally via Docker/Kubernetes with Redis BullMQ workers and PostgreSQL, guaranteeing 100% data sovereignty. Make (formerly Integromat) is a proprietary, multi-tenant cloud SaaS platform where all logic, credentials, and payload data traverse Make's managed infrastructure.

What is the fundamental difference in data flow and execution models between n8n's JSON-array pipeline and Make's bundle-based system?

n8n operates on a batch-oriented data model where every node receives and outputs an array of JSON items ([{json: {...}}]), allowing single nodes to process hundreds of records simultaneously in-memory. Make operates on an atomic 'bundle' execution model where data is passed as individual packets requiring explicit Iterators, Routers, and Aggregators where each processed bundle counts as an operation.

How do n8n and Make handle complex programmatic logic, custom scripting, and API integrations?

n8n provides native Code nodes executing sandboxed JavaScript (with npm modules) or Python with direct environment variable access, alongside a Community Node repository. Make provides a visual expression syntax with built-in functions (map(), get()) and a visual Custom App builder, but lacks direct multi-line script execution inside workflows without external webhooks.

How do the pricing models and scalability economics compare between self-hosted n8n and Make's operation-based tiers?

Self-hosted n8n offers predictable near-zero marginal execution costs limited only by host server hardware, making it cost-effective for high-frequency webhooks and IoT data ingestion. Make charges per operation and data transfer bandwidth, which can scale costs rapidly for high-throughput loops or large batch iterations.

Sources & verification

Sources checked
Content verified

Verification dates are editorial checks. Routine CMS saves and automatic updatedAt timestamps do not advance them.