Automation Platforms

Zapier vs Make vs n8n

Zapier emphasizes accessible automation across a very large app ecosystem, Make provides visual scenario building with detailed flow control, and n8n combines a visual workflow editor with code-friendly extensibility and a self-hosting option.

Editorial information reviewed Jul 18, 2026

zapier

Discover zapier, a curated resource for office productivity, slides, documents, spreadsheets, meetings, and knowledge work.

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Make

Discover Make, a curated AI resource for office productivity, research, documents, spreadsheets, and business workflows.

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n8n

Discover n8n, a curated resource for coding assistants, developer agents, AI IDEs, and software engineering tools.

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Weighted editorial profile

Compare strengths across the decisions that matter

Scores summarize documented product fit on a 1–5 scale. They are an editorial decision aid, not a performance benchmark or a promise of results.

zapier

3.5 / 5

Make

3.8 / 5

n8n

4.7 / 5

zapier Make n8n

Connector breadth

20% weight

Maintained integrations, triggers, actions, authentication, and depth per application.

zapier

5/5

Very broad app ecosystem and an accessible catalog for common business workflows.

Make

5/5

Broad integrations with detailed modules and data mapping for visual scenarios.

n8n

4/5

Strong node library plus generic HTTP, code, and community extension options.

Visual workflow building

15% weight

Branching, loops, mapping, debugging, error paths, and complex scenario readability.

zapier

4/5

Easy linear and multi-step workflows with increasingly capable branching and interfaces.

Make

5/5

Visual scenarios expose branching, routers, mapping, bundles, and execution detail.

n8n

5/5

Node canvas supports complex flows, sub-workflows, debugging, and technical control.

Developer extensibility

20% weight

Code, custom connectors, APIs, packages, source control, testing, and reusable modules.

zapier

3/5

Developer Platform and code steps extend the product within a managed ecosystem.

Make

4/5

Custom apps, APIs, webhooks, and advanced mapping support technical builders.

n8n

5/5

Code nodes, custom nodes, APIs, source-available deployment, and technical workflows are core strengths.

Hosting and data control

20% weight

Managed service, self-hosting, networking, credentials, data location, and upgrade ownership.

zapier

1/5

Managed SaaS prioritizes convenience rather than customer-operated hosting.

Make

1/5

Managed platform with enterprise controls, not a general self-hosted product.

n8n

5/5

Offers cloud and self-hosted deployment, shifting more control and operational work to the user.

AI and agent workflows

15% weight

Model nodes, tools, retrieval, memory, human approval, and agent orchestration.

zapier

4/5

AI products and a large connector ecosystem make business-tool actions accessible.

Make

4/5

AI modules and visual orchestration support multi-application AI scenarios.

n8n

5/5

AI nodes, tools, vector stores, memory, and code flexibility suit technical agent workflows.

Governance and operations

10% weight

Logs, retries, environments, permissions, auditability, support, and ownership burden.

zapier

5/5

Managed operations and enterprise administration reduce infrastructure burden.

Make

4/5

Detailed execution history and managed operation suit visual automation teams.

n8n

4/5

Strong workflow visibility, but self-hosters own availability, upgrades, security, and backups.

How to read the score

1 = limited, 2 = basic, 3 = capable, 4 = strong, 5 = category-leading for this specific workflow. Weights reflect what buyers commonly need in this category.

Scores are structured editorial judgments based on official documentation reviewed on the date shown. They measure workflow fit, breadth, control, and operating constraints—not raw model intelligence, benchmark performance, or guaranteed outcomes. Plan availability and limits can change.

Decision guide

Choose by the job you need to repeat

Start with your recurring workflow rather than the longest feature list. No product or score guarantees search, traffic, citation, or revenue results.

zapier

Best fit: Non-technical teams that value connector coverage and managed simplicity

A large app ecosystem and approachable builder make common business automations fast to launch.

Check first: Model task volume and maintain clear ownership, monitoring, naming, and recovery procedures as automation grows.

Make

Best fit: Visual builders handling branching and data-heavy cross-app workflows

Its scenario canvas exposes execution flow and mapping in a way that suits complex operational automation.

Check first: Complex visual scenarios still need modular design, test data, error handling, documentation, and cost monitoring.

n8n

Best fit: Technical teams that need extensibility, AI nodes, or deployment control

Visual orchestration combines with code, custom nodes, APIs, and an optional self-hosted runtime.

Check first: Self-hosting transfers security, availability, upgrades, backups, scaling, and incident response to your team.

Workflow comparison

A neutral summary of currently documented capabilities. Provider plans and limits can change.

Workflow comparison for zapier, Make, n8n
Decision point	zapier	Make	n8n
Best fit	Business teams automating many SaaS apps with minimal engineering.	Operations teams that need visual control over complex multi-step data flows.	Technical teams needing code, AI orchestration, private networking, or self-hosting.
Complexity model	Start simple and add paths, tables, interfaces, code, and other platform capabilities.	Scenarios expose routers, filters, bundles, mappings, iterators, and error handlers visually.	Node workflows mix visual orchestration with code, sub-workflows, credentials, and custom nodes.
Hosting	Managed SaaS with provider-operated infrastructure.	Managed SaaS with plan-specific organization and enterprise controls.	Managed n8n Cloud or customer-operated self-hosting with separate responsibilities.
Cost driver	Tasks, premium apps, users, and product-specific limits under the selected plan.	Operations, data transfer, scenario frequency, teams, and enterprise features.	Cloud executions or license plus infrastructure, storage, backups, monitoring, and engineering labor.
Reliability check	Design replay, idempotency, rate limits, alerting, and ownership for every critical Zap.	Design error routes, incomplete executions, data mapping tests, rate limits, and alerts.	Design retries, queues, scaling, secrets, backups, upgrades, monitoring, and incident response.
AI safety check	Restrict connected actions, sensitive fields, model data, and approval points.	Constrain data mapping, model prompts, action scope, and human approval branches.	Constrain tools, network, credentials, community nodes, model providers, and agent autonomy.

Comparison criteria

How we evaluate each tool in this category.

Connector coverage

Breadth and depth of maintained integrations, triggers, actions, and authentication.

Workflow building

Visual design, branching, loops, data mapping, debugging, and reusable components.

Extensibility

Code steps, custom connectors, APIs, packages, versioning, and developer workflows.

Hosting and control

Managed cloud, self-hosting, networking, credentials, data location, and upgrades.

AI automation

Agent patterns, model nodes, retrieval, tools, human approval, and observability.

Official sources checked

Capability summaries above are based primarily on provider documentation. Open the sources to confirm current availability and plan limits.

Frequently asked questions

Which is easiest: Zapier, Make, or n8n?

Zapier is often easiest for straightforward app-to-app automation, Make offers more visual control for complex scenarios, and n8n is attractive to technical teams that want extensibility or self-hosting.

Is self-hosting n8n automatically cheaper?

Not necessarily. Include infrastructure, backups, upgrades, monitoring, incident response, security, networking, and engineering time—not only license cost.

How should automation platforms be tested?

Build the same high-value workflow in each product and measure implementation time, connector gaps, operations per run, error recovery, observability, credential controls, maintainability, and monthly cost at realistic volume.