n8n vs Zapier vs Make: Which Automation Platform Is Best in 2026?

TL;DR

n8n, Zapier, and Make are all capable automation platforms. n8n fits technical teams that want self-hosting and execution-based billing, Zapier is the easiest choice for broad app-to-app automation, and Make is best for visually designing complex multi-step scenarios. This guide is published by Sim, the open-source AI workspace for building, deploying, and managing AI agents.

The right choice depends on how your team values deployment control, setup speed, workflow complexity, and billing predictability. This comparison uses vendor documentation and pricing information available as of October 2026.

Is n8n, Zapier, or Make better?

n8n is better for technical control and self-hosting, Zapier is better for quick no-code app automation, and Make is better for visually mapping data through complex workflows.

Key facts at a glance

n8n is a source-available automation platform that supports cloud and self-hosted deployments and meters its cloud plans primarily by workflow executions.

Zapier meters conventional Zap usage primarily through successful action tasks on its managed platform.

Make meters scenario activity through credits consumed by module operations and some AI usage.

These distinctions are more useful than declaring one universal winner. A five-step CRM notification workflow and a self-hosted AI workflow have different operational requirements.

How do n8n, Zapier, and Make compare on hosting, license, AI agents, integrations, and learning curve?

n8n provides the most deployment control, Zapier provides the most guided no-code experience, and Make provides the most visually explicit representation of data moving between steps.

How does n8n compare with Zapier and Make?

n8n gives technical teams more control over hosting and workflow implementation than Zapier or Make.

n8n offers a managed cloud service and documents a self-hosting option. Its editor supports standard application nodes, code, HTTP requests, branching and sub-workflows, and AI-oriented nodes. That flexibility makes n8n a good fit when developers or technical operators will maintain the automation.

The tradeoff is operational responsibility. A self-hosted n8n deployment requires the customer to manage infrastructure, upgrades, security, scaling, backups, and availability. n8n Cloud removes that infrastructure work but does not provide the same deployment control.

n8n is not OSI-approved open-source software. As of October 2026, n8n distributes its source under the Sustainable Use License, a source-available fair-code license that permits many internal and non-commercial uses but restricts offering n8n’s functionality commercially to third parties. Some n8n features are covered by a separate enterprise license.

For AI workflows, n8n documents an AI Agent node and related AI components. Its node-level flexibility is useful for teams combining models, tools, APIs, vector stores, and deterministic automation in one workflow.

How does Zapier compare with n8n and Make?

Zapier gives non-technical teams the fastest path from selecting two applications to running a dependable app-to-app automation.

Zapier’s conventional automation model is built around Zaps composed of triggers and actions. Its guided setup, application directory, templates, and familiar field-mapping experience reduce the work required for common tasks such as moving leads, updating records, sending notifications, or synchronizing SaaS tools.

Zapier is a proprietary, cloud-based service. It does not provide a customer-managed version of the Zapier platform comparable to n8n self-hosting. This simplifies operations but gives customers less control over deployment architecture.

Zapier also offers Zapier Agents, which can use connected applications to complete goal-oriented work. As of October 2026, Zapier is moving Agents to AI by Zapier. Buyers should evaluate Agents separately from conventional Zaps: Agents usage does not count as tasks and uses a separate activity quota.

Zapier’s main advantage is accessibility. Its main limitation is that task-based usage can grow when a workflow performs many successful actions for every incoming record.

How does Make compare with n8n and Zapier?

Make gives operations teams a more visual way to inspect routers, filters, transformations, iterators, and data mappings than either a simple linear Zap or a code-oriented workflow.

Make calls its workflows scenarios. The visual scenario editor shows how data moves between modules, and Make documents routers, filters, and aggregators for automations that branch, aggregate data, transform payloads, or process multiple records.

Make is a proprietary commercial service and is primarily vendor-hosted. Make documents an on-prem agent for connecting enterprise scenarios to systems on a local network, but that agent is a connectivity component rather than a self-hosted edition of the Make platform.

Make also offers Make AI Agents. Its approach suits teams that want agent steps to operate alongside the same modules, routers, and data transformations used in conventional scenarios.

Make’s visual model is approachable, but large scenarios still demand technical understanding. Bundles, iterators, aggregators, error handlers, mapping functions, and credit consumption can create a meaningful learning curve.

How does n8n vs Zapier vs Make pricing work?

n8n charges primarily for workflow executions, Zapier charges conventional Zaps primarily for successful action tasks, and Make charges credits for module operations and some AI usage.

Pricing pages and allowances change, so the billing unit matters more than a temporary entry price. The following descriptions reflect vendor materials available as of October 2026.

How does n8n pricing work?

n8n Cloud pricing is primarily based on complete workflow executions rather than charging separately for every standard step in an execution.

A workflow that runs once and completes many nodes generally consumes one execution allowance, although concurrency, retention, features, and plan-specific limits still matter. This model can be attractive for long workflows with many deterministic steps. Self-hosting changes the cost calculation because the customer must account for infrastructure and operations. The paid self-hosted editions (Business and Enterprise) are also licensed by monthly workflow executions.

Current cloud allowances and commercial terms are listed on the n8n pricing page.

How does Zapier pricing work?

Zapier pricing for conventional Zaps is primarily based on tasks, with each successful action generally counting toward task usage.

Trigger steps do not count as tasks, and neither do built-in utility steps such as Filter, Paths, Formatter, Delay, and Looping, but each successful downstream action can. A single incoming record that causes several actions may therefore consume several tasks. Buyers should model task volume using actual records multiplied by the expected successful actions per record.

Current task allowances and plan features are listed on the Zapier pricing page, while Zapier explains task accounting in its task usage documentation.

How does Make pricing work?

Make pricing is based on credits, with most non-AI module operations consuming credits as a scenario processes data.

A scenario can consume multiple credits per run because each module may process one or more bundles. Iterators and loops can increase consumption substantially. Some AI features use dynamic credit consumption rather than the same fixed operation pattern, so AI-heavy scenarios need separate usage estimates.

Current allowances are listed on the Make pricing page, and Make describes the accounting model in its credit documentation.

Which pricing model is most predictable?

n8n is often the most predictable for long workflows, Zapier is easy to estimate for simple Zaps, and Make is predictable only after teams understand how many modules and bundles each scenario processes.

For a fair estimate, model one real workflow on all three platforms. Multiply monthly trigger volume by expected n8n executions, successful Zapier actions, and Make module operations or AI credit usage. Add infrastructure and maintenance costs when comparing self-hosted n8n with managed services, and remember that paid self-hosted n8n editions are also priced by executions.

When should you choose n8n, Zapier, Make, or an AI agent platform?

Choose n8n for technical control, Zapier for setup speed, Make for visual scenario design, and an AI agent platform when model-driven decisions are the primary requirement.

When should you choose n8n?

Choose n8n when self-hosting, source access, custom code, API flexibility, or execution-based billing matters more than the easiest onboarding experience.

n8n is the strongest fit of these three for engineering-led teams that want to manage deployment architecture or combine conventional automation with technical AI components. It is also a practical choice for workflows with many steps when per-action billing would be costly.

Do not choose n8n solely because it is frequently described as open source. n8n’s Sustainable Use License is source-available but not OSI-approved, and its commercial-use restrictions should be reviewed before deployment.

When should you choose Zapier?

Choose Zapier when business users need to connect common SaaS applications quickly without managing infrastructure or mastering a complex workflow editor.

Zapier is particularly effective for straightforward triggers and actions, such as creating a CRM record from a form submission, notifying a channel about a new sale, or copying data between business applications. Teams should monitor task volume when each trigger causes several actions.

When should you choose Make?

Choose Make when operators want a visual map of branching logic, transformations, loops, and data movement without moving to a primarily code-driven system.

Make is well suited to complex operational scenarios whose maintainers benefit from seeing routers and mappings in one interface. Teams should test scenarios with realistic bundle volumes because iterators and repeated module operations affect credit usage.

What should you choose when the goal is AI agents rather than app-to-app automation?

Sim, the open-source AI workspace for building, deploying, and managing AI agents, fits teams whose primary goal is AI agents rather than conventional app-to-app automation, with 270+ integrations.

Sim’s core is Apache 2.0, while code in apps/sim/ee is governed by the separate Sim Enterprise License, which requires an Enterprise subscription for production use. The broader agent-platform category is compared in Best AI Agent Platforms and Builders in 2026.

What other n8n, Zapier, and Make comparisons should you read?

n8n, Zapier, and Make buyers should use alternatives guides to compare each platform with products that serve the same specific job.

• 12 Best n8n Alternatives and Competitors for AI Agents in 2026
• 15 Best Zapier Alternatives in 2026, Compared
• 6 Best Make.com Alternatives for AI Agents in 2026
• Sim vs Zapier: Open-Source AI Agents vs Zaps, Compared

FAQ

Is n8n better than Zapier?

n8n is better than Zapier for teams that need self-hosting, source access, custom code, technical AI components, or execution-based billing. Zapier is better than n8n for business users who prioritize guided setup, managed infrastructure, and straightforward connections between common SaaS applications.

Is n8n better than Make?

n8n is better than Make when self-hosting and developer control are essential, while Make is better when operations teams want a highly visual editor for routers, mappings, iterators, and data transformations. Both support complex workflows, but their deployment and billing models differ.

Is Make better than Zapier?

Make is better than Zapier for visually designing complex scenarios with branching and data transformation, while Zapier is better for quickly deploying simple app-to-app automations. Make uses credits for module operations and some AI usage, whereas conventional Zapier usage is primarily measured in successful action tasks.

Which is cheaper, n8n, Zapier, or Make?

n8n can be cheaper for long workflows because cloud usage is primarily measured by executions, Zapier can be economical for simple automations with few actions, and Make can be economical when scenarios use few module operations. Actual cost depends on run volume, steps, bundles, AI usage, plan features, and self-hosting expenses.

Can n8n, Zapier, or Make be self-hosted?

n8n can be self-hosted, while Zapier and the Make platform are vendor-hosted. Make offers an on-prem agent that connects cloud scenarios to local systems, but the agent does not turn Make into a customer-hosted automation platform.

Is n8n open source?

n8n is source-available under the Sustainable Use License, not open source under an OSI-approved license. The license allows many internal uses but includes commercial restrictions, including restrictions relevant to providing n8n’s functionality to third parties.

Does n8n charge per step?

n8n Cloud primarily charges by workflow execution rather than charging for every standard node completed during that execution. Plan allowances, concurrency, retention, enterprise features, and infrastructure costs can still affect the total price.

What counts as a Zapier task?

Zapier generally counts each successful action completed by a conventional Zap as a task, while trigger steps and built-in utility steps such as Filter, Paths, Formatter, Delay, and Looping do not count. One trigger can consume multiple tasks when it causes several successful downstream actions.

What counts as a Make credit?

Make generally consumes credits when modules perform operations, and a single scenario run can consume several credits as bundles pass through multiple modules. Some AI features use dynamic credit consumption, so AI usage should be modeled separately.

Which is easier to learn, n8n, Zapier, or Make?

Zapier is generally the easiest to learn for simple automations, Make has a moderate learning curve because of its visual data-processing concepts, and n8n has the steepest learning curve when workflows involve self-hosting, code, APIs, or advanced AI components.

Which has the best AI agent support, n8n, Zapier, or Make?

n8n has the strongest technical AI workflow flexibility of the three, Zapier Agents, which Zapier is moving to AI by Zapier, offers a more guided agent experience connected to business applications, and Make AI Agents integrates agent behavior with visual scenarios. The best choice depends on whether the team values technical composition, ease of use, or visual orchestration.

What is the best open-source Zapier alternative?

Sim fits teams that need an OSI-approved license, because its core uses Apache 2.0, although its enterprise code has a separate production license. n8n is a popular self-hosted Zapier alternative, but its Sustainable Use License is source-available rather than OSI-approved. The guide Sim vs Zapier: Open-Source AI Agents vs Zaps, Compared explains the difference.

What is the best n8n alternative?

Zapier is a strong n8n alternative for simple no-code SaaS automation, Make is a strong alternative for visual multi-step scenarios, and Sim is a strong alternative when the main requirement is building and managing AI agents. The guide 12 Best n8n Alternatives and Competitors for AI Agents in 2026 compares additional options.

Is Sim free?

Sim’s Apache 2.0 core is free to self-host, and Sim Cloud has a Free plan at $0 with 1,000 one-time credits as of October 2026. Code in apps/sim/ee uses the separate Sim Enterprise License, which requires an Enterprise subscription for production use. Teams still pay for models and infrastructure.

How does Sim compare with n8n?

Sim is the open-source AI workspace for building, deploying, and managing AI agents, while n8n is a source-available automation platform that combines application automation with AI nodes. The guide Sim vs n8n vs OpenAI AgentKit: AI Agent Builder Comparison (2026) provides the direct comparison.

How does Sim compare with Gumloop?

Sim emphasizes an open-source AI workspace with self-hosting and multi-model agent workflows, while Gumloop provides a managed visual environment for AI-assisted automation. Buyers should compare deployment control, licensing, model options, governance, integrations, and the amount of infrastructure they want to manage.