Software comparison
n8n vs Make vs Zapier
For a non-technical small business, automation should remove a repeated admin task without creating a fragile system nobody knows how to fix. Zapier is often the easiest starting point for straightforward app-to-app connections, Make gives more visual control over branching workflows, and n8n offers flexibility when someone can own its technical setup. Compare the full workflow—including failures and ongoing maintenance—not just how quickly a demo works.
Independent research · Verify current pricing with each provider
Pricing reality
Pricing and execution quotas change often and can depend on task volume, workflow runs, hosting and plan tier. This guide explains decision criteria rather than quoting a fixed monthly cost. Confirm current limits and terms on the official product pages.
At a glance
Which one fits?
Best for: Technical users who want flexible workflows, custom logic and a self-hosting option
Free: Review the current cloud trial or plan and the separate self-hosted Community Edition requirements.
Best for: Visual workflows with branching, data mapping and multi-step scenarios
Free: Check current free monthly credits, operation rules and scheduling limits.
Best for: Quickly connecting common SaaS apps with a low setup burden
Free: Check current free task limits, polling intervals and multi-step workflow restrictions.
Detailed review
What to know before you choose.
n8n
Best for Technical users who want flexible workflows, custom logic and a self-hosting option
Free plan and limits
Review the current cloud trial or plan and the separate self-hosted Community Edition requirements.
The Trade-off
Self-hosting adds responsibility for updates, credentials, backups, uptime, monitoring and security.
Make
Best for Visual workflows with branching, data mapping and multi-step scenarios
Free plan and limits
Check current free monthly credits, operation rules and scheduling limits.
The Trade-off
Complex scenarios can become difficult to debug, and operation-based billing needs realistic volume estimates.
Zapier
Best for Quickly connecting common SaaS apps with a low setup burden
Free plan and limits
Check current free task limits, polling intervals and multi-step workflow restrictions.
The Trade-off
Higher-volume or branching workflows can become costly; confirm the exact task-counting rules first.
Before automating a business process
Design for failures, not just the happy path.
- Write down the trigger, expected inputs, output and owner of the workflow.
- Define what happens when an API times out, returns duplicate data or hits a rate limit.
- Use idempotency or deduplication for actions that send messages, create invoices or update records.
- Store credentials in the platform's supported secret mechanism; never paste keys into prompts or public workflow exports.
- Log failures, alert a responsible person and test a recovery path before enabling the workflow for real customers.
- Estimate monthly volume and include hosting, AI/API charges, retries and maintenance in total cost.
The billing model changes the decision
Compare how each platform counts a real workflow.
Do not compare plan quotas as if a task, credit and execution were the same unit. Estimate the cost using the actual records, branches, AI calls and successful actions your process will run.
| Platform | Usage unit | What to estimate | Main trade-off |
|---|---|---|---|
| Zapier | Successful action steps consume tasks; triggers and some built-in steps do not. | Records processed × successful action steps, plus repeated runs and AI step rates. | Straightforward to adopt, but action-heavy workflows can use tasks quickly. |
| Make | Credits; ordinary operations commonly use one credit, while some AI features vary. | Module runs, bundles/records, branching and whether AI usage is token-based. | Visual control, but you need to understand the scenario's actual credit consumption. |
| n8n | Cloud plans are based on workflow executions, not the number of steps inside a run. | How many times the workflow starts, plus AI/API costs and any self-hosting overhead. | Flexible execution model; self-hosting shifts maintenance and security work to your team. |
Illustration: if 1,000 records each pass through three successful Zapier action steps, those actions could use about 3,000 tasks before accounting for other actions or repeated runs. A comparable Make scenario must be estimated from its module and credit rules; an n8n workflow triggered once per record would count about 1,000 executions. Your real design may differ, so test it with representative data.
Official documentation to check before choosing
- Zapier task counting ↗
Review what counts as a task and how plan limits affect runs.
- Make credit rules ↗
Understand fixed and dynamic credit use, including AI-related usage.
- n8n Cloud plan limits ↗
Check execution allowances and plan-specific features.
A practical selection test
- Build the same small workflow in each platform using test records.
- Run enough sample records to reveal branches, retries and duplicate handling.
- Record actual task/credit/execution use and the time needed to debug a failed run.
- Calculate monthly cost at expected volume, including any AI provider charges and hosting.
- Choose the simplest platform that meets your reliability and control requirements.
Continue exploring
StackPick verdict
The bottom line.
Choose Zapier if nobody on the team wants to maintain infrastructure and your workflow is supported by its integrations. Choose Make when you need more visible branching and data transformation and can test scenarios carefully. Choose n8n when custom logic or self-hosting is a genuine requirement and a named person can own updates, credentials, backups and monitoring. If the process is not documented and stable when done manually, fix that first instead of automating the confusion.
Keep exploring
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