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Comparison4 min read

Zapier vs Make vs n8n, which automation platform fits your team

A side-by-side look at Zapier, Make and n8n covering ease of use, workflow complexity, pricing structure, hosting and AI features.

Zapier, Make and n8n all connect apps and automate repetitive work, and all three now include features for building AI-assisted workflows. They differ in who they are designed for, how they model a workflow, how they charge, and where they run. This comparison focuses on those differences so you can match a platform to your team rather than to a feature list.

At a glance

ZapierMaken8n
Primary audienceNon-technical teams and operationsOperations teams and power usersTechnical teams and developers
Workflow modelLinear steps with paths and filtersVisual canvas of modules and routesNode-based canvas with code nodes
App integrationsLargest catalogLarge catalogSmaller catalog, plus generic HTTP and code
Pricing basisTasks per month, tiered plansOperations or credits per monthExecutions; free self-hosted community edition
HostingCloud onlyCloud onlyCloud or self-hosted
Custom codeLimited code stepsLimited, via functions and HTTPFull JavaScript and Python nodes
Learning curveLowestModerateHighest

Zapier

Zapier is the most widely adopted of the three and has the largest library of prebuilt app integrations. A workflow, called a Zap, starts with a trigger and runs a sequence of actions, with paths and filters for branching. The interface is designed so that someone with no technical background can build a working automation in minutes.

</div>
<p class="tool-card__desc">No-code automation connecting thousands of apps with triggers, actions and AI steps.</p>
<div class="tool-card__foot">
  <span class="price-tag">Freemium</span>
  <a class="btn btn--secondary btn--sm" href="/go/zapier?p=embed-zapier-vs-make-vs-n8n" rel="nofollow noopener" target="_blank" data-out="zapier">Visit website<svg class="i" width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.8" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M14 4h6v6M20 4l-9 9M18 14v5a1 1 0 0 1-1 1H5a1 1 0 0 1-1-1V7a1 1 0 0 1 1-1h5"/></svg></a>
</div>

Strengths

  • Very broad integration catalog, including many niche business apps
  • Fast setup for straightforward trigger-action workflows
  • Additional products such as tables, forms and AI agents in the same account

Limitations

  • Task-based pricing can rise quickly for high-volume or many-step workflows
  • Complex logic with loops and heavy data transformation is harder to express and debug
  • Cloud only, which may not suit strict data residency requirements

Make

Make, formerly Integromat, uses a visual canvas where each module is a node and data flows between them. Routers, iterators and aggregators make it easier to handle arrays, branching and data transformation than in a linear step model. Many teams move to Make when their Zapier workflows become complicated.

</div>
<p class="tool-card__desc">Visual automation platform for building complex multi-app scenarios on a canvas.</p>
<div class="tool-card__foot">
  <span class="price-tag">Freemium</span>
  <a class="btn btn--secondary btn--sm" href="/go/make?p=embed-zapier-vs-make-vs-n8n" rel="nofollow noopener" target="_blank" data-out="make">Visit website<svg class="i" width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.8" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M14 4h6v6M20 4l-9 9M18 14v5a1 1 0 0 1-1 1H5a1 1 0 0 1-1-1V7a1 1 0 0 1 1-1h5"/></svg></a>
</div>

Strengths

  • Visual canvas that shows complex flows clearly
  • Strong data manipulation, including iterating over lists and mapping nested fields
  • Generally more operations per plan for comparable workloads

Limitations

  • Steeper learning curve, particularly around data structures and error handling
  • Each module execution counts toward usage, so polling triggers and large loops need planning
  • Cloud only

n8n

n8n is a workflow automation tool with a fair-code licence. The community edition can be self-hosted, and a managed cloud service is also available. Its node-based editor looks similar to Make's, but it is aimed at technical users: any node can be followed by JavaScript or Python code, and the HTTP Request node makes it straightforward to call APIs without a dedicated integration. It has become a popular choice for AI agent workflows because of its LangChain-based AI nodes and support for connecting to models and vector stores.

</div>
<p class="tool-card__desc">Fair-code workflow automation with self-hosting, custom code and AI agent nodes.</p>
<div class="tool-card__foot">
  <span class="price-tag">Open source</span>
  <a class="btn btn--secondary btn--sm" href="/go/n8n?p=embed-zapier-vs-make-vs-n8n" rel="nofollow noopener" target="_blank" data-out="n8n">Visit website<svg class="i" width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.8" stroke-linecap="round" stroke-linejoin="round" aria-hidden="true"><path d="M14 4h6v6M20 4l-9 9M18 14v5a1 1 0 0 1-1 1H5a1 1 0 0 1-1-1V7a1 1 0 0 1 1-1h5"/></svg></a>
</div>

Strengths

  • Self-hosting gives control over data, network access and cost at scale
  • Code nodes remove most limits on custom logic
  • Pricing based on workflow executions rather than individual steps

Limitations

  • Self-hosting means you own upgrades, backups, scaling and security
  • Fewer prebuilt integrations, so some connections require HTTP configuration
  • Less approachable for non-technical colleagues

How they handle common scenarios

ScenarioBest fitWhy
Marketing team syncing form leads to a CRM and SlackZapierFastest to build, integrations exist for nearly every tool
Processing order data with loops, lookups and formattingMakeIterators and aggregators handle list data cleanly
Internal tools calling private APIs behind a firewalln8nSelf-hosted instance can reach internal networks
High-volume, multi-step workflows on a fixed budgetn8n or MakeExecution- or operation-based pricing scales more predictably
AI agent that reads tickets and drafts repliesAny, with caveatsZapier for simplicity, n8n for control over models and data

Pricing structure

All three offer free entry points. Zapier and Make have free plans with limited monthly usage and tiered paid plans billed on tasks or operations. n8n's community edition is free to self-host, while its cloud plans are billed by workflow executions. The key difference is what counts as a billable unit: Zapier counts each successful action step, Make counts module operations, and n8n counts a full workflow run. A ten-step workflow can therefore cost very differently across platforms. Model your expected volume against each vendor's current plan page before deciding.

Questions to ask before choosing

  1. Who will build and maintain the workflows: operations staff or engineers?
  2. Do any workflows need to reach systems inside a private network?
  3. How many runs per month, and how many steps per run, do you expect?
  4. Are there data residency or compliance requirements that rule out a cloud-only tool?
  5. Which of your critical apps have native integrations on each platform?

Verdict

Choose Zapier when ease of use and integration coverage matter most and volumes are moderate. Choose Make when workflows involve real data manipulation and you want a visual view of complex logic. Choose n8n when your team is technical, wants to self-host, or needs custom code and AI workflows without per-step costs. Many organisations use two of these side by side, typically Zapier for business teams and n8n for engineering.

Compare full profiles for Zapier, Make and n8n, or look at Pipedream as a developer-oriented alternative.

Tools in this article

  1. Zapier

    No-code automation connecting thousands of apps with triggers, actions and AI steps.

    Automation Freemium Visit
  2. Make

    Visual automation platform for building complex multi-app scenarios on a canvas.

    Automation Freemium Visit
  3. n8n

    Fair-code workflow automation with self-hosting, custom code and AI agent nodes.

    Automation Open source Visit

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