n8n vs Make vs Zapier: which automation tool fits your team?

Zapier is the easiest of the three to start with and has the largest app catalog; its pricing page cites 9,000+ apps. Make gives you a visual canvas that handles branching, loops, and data transformation well, and its pricing page lists 3,000+ native apps. n8n is the developer's choice: code steps in JavaScript or Python, an AI Agent node that connects chat models to tools, billing per workflow run, and the option to self-host.

None of them is best in general. The right pick depends on who will build and maintain the workflows, how your volume interacts with each billing model, and whether data has to stay on infrastructure you control. Many teams end up using two: Zapier or Make for quick automations that operators build, and n8n or custom code for heavy, technical workflows.

The sections below compare the three on hosting, billing, connectors, AI features, error handling, version control, team features, and learning curve, then give a verdict by team type. Facts about plans and features were checked against each vendor's pricing pages and documentation on October 31, 2026.

Zapier and Make are cloud services. You cannot run either on your own servers, although Make's Enterprise plan offers an on-premise agent that lets scenarios reach applications and databases on your local network without changing your firewall settings. If your requirement is only to reach an internal system, that may be enough.

n8n runs either on n8n's cloud or on your infrastructure. The self-hosted Community edition is free under the Sustainable Use License, which allows internal business use but restricts offering n8n commercially to others. It includes almost the whole product, but leaves out SSO, Git-based version control, environments, sharing of workflows and credentials, log streaming, and external secrets. n8n's Business plan is self-hosted only, and Enterprise can be hosted or self-hosted.

Self-hosting is a responsibility, not just a price. Someone owns upgrades, backups, queue workers, monitoring, and security patches. Teams with a platform engineer absorb that easily; teams without one should price a hosted plan before assuming self-hosting is cheaper.

Zapier counts a task each time an action completes successfully. Triggers, polling, and built-in tools such as Formatter and Paths do not count, failed actions are not counted, and AI steps can use more than one task depending on the model tier. Make counts credits: most module actions use one credit, every module inside a loop runs once per item, and error handlers and the Router do not consume credits. When a Make account runs out of credits, scenarios stop until more are added. n8n counts executions: one run of a whole workflow is one execution, however many steps it has, and plans include unlimited users and workflows.

As an illustration, take a workflow with a trigger and five actions that runs 2,000 times a month. Under Zapier's rules that is roughly 10,000 tasks if every action succeeds and none are Formatter or Paths steps. Under Make's rules it is at least 10,000 credits for the actions, more if the trigger module or an iterator adds work. Under n8n's rules it is 2,000 executions. Those unit counts are not prices: compare what each vendor charges for that volume on the plan you would actually need, then add AI model costs.

The models reward different shapes. n8n favors long workflows with many steps per run. Zapier's free built-in steps favor workflows heavy on formatting and branching. Make rewards careful scenario design, because filtering early and avoiding unnecessary iterations cuts credits directly.

Zapier's catalog is the broadest, which matters most for niche SaaS tools where a prebuilt trigger saves real work. It offers webhooks on paid plans and Code by Zapier for small scripts, with longer runtimes on paid plans. Make covers fewer apps, and its HTTP module and custom apps let you reach any service with a public API. n8n's integration library is smaller than Zapier's, but its HTTP Request node, Code node, and community nodes mean a developer is rarely blocked.

Check the specific triggers and actions you need, not the logo count. A connector that exists but cannot filter by the field you care about, or polls when you need an instant webhook, may be worse than a well-built HTTP call. Zapier's polling interval depends on plan, from 15 minutes on Free to 1 minute on Team and Enterprise, which matters for lead response and other time-sensitive workflows.

All three now treat AI as a step inside a workflow rather than a separate product. Zapier's AI by Zapier step works with OpenAI, Anthropic, Google Gemini, Azure OpenAI, and Amazon Bedrock models, returns structured output fields, and can call tools as an agent, with an option to require approval before a tool runs. Zapier is migrating its standalone Agents product into these steps. Make has an AI Agents app where an agent gets instructions, knowledge, and tools drawn from modules, scenarios, or MCP. n8n's AI Agent node connects a chat model to one or more tool sub-nodes, and companion nodes cover extraction, classification, and retrieval.

The difference that matters in practice is control. n8n lets you choose the model provider, run self-hosted models, and inspect every intermediate step in the execution log. Zapier gives you the simplest setup and bills AI in the same tasks as everything else, scaled by model tier. Make sits between them, with visual control over what the agent can touch.

For any agent that writes to a system of record, keep a deterministic validation step and an approval path, whatever the platform. If the job is reading emails and documents, our Zapier Email Parser alternatives guide covers extraction patterns in more detail.

Zapier lets you add an error handler to any step, which splits the Zap into a success path and an error path, and Zap history lets you replay errored runs manually or automatically. Make's error handlers are more granular: Skip, Retry, Resume with a substitute value, Commit, and Rollback. Its incomplete executions feature stores a failed run so it can be retried or resolved later, but it is off by default, so turn it on for any scenario that touches money or customer records.

n8n handles failure at the workflow level. You assign an error workflow, which starts with an Error Trigger node and receives the failed execution's details, and the Stop And Error node lets you fail a run deliberately when data looks wrong. For debugging, n8n can load data from a previous execution into the editor so you can re-run a failure step by step, which developers tend to prefer to reading run logs.

Whichever you choose, decide where alerts go and who answers them. An error path that posts to a channel nobody watches is the same as no error handling.

Zapier creates a new version each time you publish, and drafts let you edit a running Zap without turning it off. Version history retention depends on plan: one month on Professional, six months on Team, and one year on Enterprise. Make's scenario history records each run plus user changes such as edits, scheduling changes, and activation, which shows who changed what, but it is not Git.

n8n is the only one of the three with Git-based source control, which connects instances to a repository so each environment maps to a branch. It requires a Business or Enterprise plan. Without it, n8n keeps workflow history in its own database, with full history on Enterprise. If your team reviews changes in pull requests and promotes from staging to production, n8n's paid editions or a custom codebase are the options that fit that habit.

Zapier's Team plan adds shared workspaces, shared app connections, folder permissions, SAML single sign-on, and audit logs. Enterprise adds SCIM provisioning, app access controls, custom data retention, and log streams. Make offers Teams and Enterprise plans, and its Enterprise plan includes the on-premise agent. n8n includes unlimited users on every plan, with SSO and LDAP on Business and Enterprise, and audit logging, log streaming, and external secret stores on Enterprise.

For regulated data, ask each vendor for its current security documentation and data processing terms, and decide where execution logs live, because those logs often contain the customer data that flowed through the workflow. Self-hosted n8n keeps logs on your infrastructure, which simplifies some reviews and adds responsibility for securing them.

Zapier has the gentlest curve. A Zap reads top to bottom like a checklist, and an operations person can build a useful one in an afternoon. The cost shows up later, when dozens of Zaps built by different people overlap and nobody owns the whole picture.

Make asks more of the builder. You need to understand bundles, iterators, aggregators, and mapping between modules, but the canvas makes complex flows easier to follow once they are built. It suits people who think visually and are comfortable with data structures.

n8n assumes comfort with JSON, expressions, and sometimes code. In exchange, a developer can do almost anything and, on paid plans, manage workflows in Git like other software. If nobody on the team reads JSON, n8n will be hard to maintain no matter how good its pricing looks.

Use the team that will own the workflows a year from now as the deciding factor, not the person who builds the first one. Then run your most important workflow in your top two candidates with real data before you move anything else.

• Solo founder or small non-technical team: Zapier, unless cost at your volume clearly favors Make.
• Operations or marketing team running complex, branching workflows: Make.
• Startup with engineers, or any team that wants code steps and per-run billing: n8n Cloud.
• Data must stay on your servers or in your region: self-hosted n8n, with a named owner for upgrades and backups.
• Enterprise with SSO, SCIM, and audit requirements: Zapier Enterprise or n8n Enterprise, and compare Workato and Power Automate too.
• Agency building automations for clients: Make or n8n, and read n8n's license before hosting n8n for clients.
• A workflow that needs its own screens, approvals, and database: none of the three; scope custom software.

Workflow builders are good at moving data between systems. They are weaker when the workflow is the product: when several people need to review records, approve exceptions, and see status in one place, or when the logic has grown large enough that nobody can follow it on a canvas. At that point, the choice between n8n, Make, and Zapier matters less than the decision to give the process its own system.

A focused custom tool keeps the same integrations but adds a database, a review interface, logging, and tests. Our custom software cost guide puts most focused internal tools between $15K and $75K for a first production version; compare that with several years of subscriptions and repair time. Our Zapier alternatives guide covers the wider field, including Power Automate, Workato, and Activepieces, and our business process automation guide helps you decide which processes are worth automating at all.