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.
By GetSkillary Editorial · Updated
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
Zapier
Make
n8n
Primary audience
Non-technical teams and operations
Operations teams and power users
Technical teams and developers
Workflow model
Linear steps with paths and filters
Visual canvas of modules and routes
Node-based canvas with code nodes
App integrations
Largest catalog
Large catalog
Smaller catalog, plus generic HTTP and code
Pricing basis
Tasks per month, tiered plans
Operations or credits per month
Executions; free self-hosted community edition
Hosting
Cloud only
Cloud only
Cloud or self-hosted
Custom code
Limited code steps
Limited, via functions and HTTP
Full JavaScript and Python nodes
Learning curve
Lowest
Moderate
Highest
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.
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.
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.
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
Scenario
Best fit
Why
Marketing team syncing form leads to a CRM and Slack
Zapier
Fastest to build, integrations exist for nearly every tool
Processing order data with loops, lookups and formatting
Make
Iterators and aggregators handle list data cleanly
Internal tools calling private APIs behind a firewall
n8n
Self-hosted instance can reach internal networks
High-volume, multi-step workflows on a fixed budget
n8n or Make
Execution- or operation-based pricing scales more predictably
AI agent that reads tickets and drafts replies
Any, with caveats
Zapier 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
Who will build and maintain the workflows: operations staff or engineers?
Do any workflows need to reach systems inside a private network?
How many runs per month, and how many steps per run, do you expect?
Are there data residency or compliance requirements that rule out a cloud-only tool?
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.
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