[{"data":1,"prerenderedAt":51},["ShallowReactive",2],{"insight-en-n8n-vs-make-vs-zapier":3},{"html":4,"toc":5,"faq":33,"faqTitle":49,"words":50},"\u003Cp>Every "n8n vs Make vs Zapier" comparison you will find is written by one of three people: a vendor, an affiliate, or someone who tried each tool for an afternoon. We have shipped production workflows on all three for clients, and we run n8n inside our own products. This is the comparison we give clients when they ask which one to pick.\u003C/p>\n\u003Cp>The short version: \u003Cstrong>Zapier is the fastest way to connect two apps, Make is the best visual builder for mid-complexity flows, and n8n is the right choice once volume, data control or custom logic start to matter.\u003C/strong> The rest of this article explains where those lines fall.\u003C/p>\n\u003Ch2 id=\"section-1\">The comparison at a glance\u003C/h2>\n\u003Cdiv class=\"prose__table\">\u003Ctable>\u003Cthead>\u003Ctr>\u003Cth>\u003C/th>\u003Cth>Zapier\u003C/th>\u003Cth>Make\u003C/th>\u003Cth>n8n\u003C/th>\u003C/tr>\u003C/thead>\u003Ctbody>\u003Ctr>\u003Ctd>Best at\u003C/td>\u003Ctd>Simple app-to-app automations\u003C/td>\u003Ctd>Visual, branching data flows\u003C/td>\u003Ctd>Complex, high-volume and AI workflows\u003C/td>\u003C/tr>\n\u003Ctr>\u003Ctd>Hosting\u003C/td>\u003Ctd>Cloud only\u003C/td>\u003Ctd>Cloud only\u003C/td>\u003Ctd>Cloud or self-hosted\u003C/td>\u003C/tr>\n\u003Ctr>\u003Ctd>How you pay\u003C/td>\u003Ctd>Per task (each action that runs)\u003C/td>\u003Ctd>Per operation (each module run)\u003C/td>\u003Ctd>Per workflow execution on cloud; infrastructure only when self-hosted\u003C/td>\u003C/tr>\n\u003Ctr>\u003Ctd>Integrations\u003C/td>\u003Ctd>The largest library by far\u003C/td>\u003Ctd>Large library\u003C/td>\u003Ctd>Smaller native library, plus any HTTP API\u003C/td>\u003C/tr>\n\u003Ctr>\u003Ctd>Custom code\u003C/td>\u003Ctd>Limited code steps\u003C/td>\u003Ctd>Limited, through custom functions and HTTP modules\u003C/td>\u003Ctd>Full JavaScript and Python code nodes\u003C/td>\u003C/tr>\n\u003Ctr>\u003Ctd>Learning curve\u003C/td>\u003Ctd>Lowest\u003C/td>\u003Ctd>Moderate\u003C/td>\u003Ctd>Moderate to steep\u003C/td>\u003C/tr>\n\u003Ctr>\u003Ctd>Data stays in your infrastructure\u003C/td>\u003Ctd>No\u003C/td>\u003Ctd>No\u003C/td>\u003Ctd>Yes, when self-hosted\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/div>\n\u003Ch2 id=\"section-2\">Pricing models decide more than features\u003C/h2>\n\u003Cp>The pricing model is the most underrated difference between the three, because it changes which workflows are affordable to build at all.\u003C/p>\n\u003Cp>\u003Cstrong>Zapier charges per task.\u003C/strong> Every action step that successfully runs counts. A Zap with one trigger and five actions uses five tasks each time it fires.\u003C/p>\n\u003Cp>\u003Cstrong>Make charges per operation.\u003C/strong> Every module that runs counts, including routers, iterators and aggregators. A flow that loops over 100 order lines and touches each one three times uses hundreds of operations per run.\u003C/p>\n\u003Cp>\u003Cstrong>n8n Cloud charges per workflow execution\u003C/strong>, regardless of how many steps the workflow has. \u003Cstrong>Self-hosted n8n\u003C/strong> costs nothing per execution: you pay for the server.\u003C/p>\n\u003Cp>What this means in practice:\u003C/p>\n\u003Cul>\n\u003Cli>A short workflow that runs a few hundred times a month is cheap anywhere. Pick on convenience.\u003C/li>\n\u003Cli>A long workflow with many steps, or one that loops over lists, is where Zapier and Make bills grow quickly. The same logic on n8n costs one execution per run, or only server time when self-hosted.\u003C/li>\n\u003Cli>High-volume, event-driven automation, such as processing every order, every inbound email or every crawled page, is where self-hosted n8n usually wins by a wide margin.\u003C/li>\n\u003C/ul>\n\u003Cp>Check each vendor's current pricing page before deciding. Plans and limits change, but the unit each one charges for has been stable, and the unit is what drives cost at scale.\u003C/p>\n\u003Ch2 id=\"section-3\">Hosting and data control\u003C/h2>\n\u003Cp>Zapier and Make are software-as-a-service only. Your data passes through their infrastructure, which is fine for most marketing and sales automation.\u003C/p>\n\u003Cp>n8n can run on your own server, in your own cloud account, or inside a private network. That matters when:\u003C/p>\n\u003Cul>\n\u003Cli>You handle personal, health or financial data and need to control where it is processed.\u003C/li>\n\u003Cli>You operate in a region with data-residency rules.\u003C/li>\n\u003Cli>The systems you automate are internal and not reachable from the public internet.\u003C/li>\n\u003Cli>You are in a market where paying for foreign SaaS is difficult, or where a vendor's service is not available.\u003C/li>\n\u003C/ul>\n\u003Cp>Self-hosting is not free of work. Someone has to handle updates, backups, monitoring and scaling. For a single small workflow, that overhead is not worth it. For an automation layer the business depends on, it usually is.\u003C/p>\n\u003Ch2 id=\"section-4\">Complexity and custom logic\u003C/h2>\n\u003Cp>\u003Cstrong>Zapier\u003C/strong> is built around linear flows. It has filters, paths and formatter steps, and they cover a surprising amount of ground. Once a workflow needs loops over data, complex branching or real error handling, Zapier starts to feel like a workaround.\u003C/p>\n\u003Cp>\u003Cstrong>Make\u003C/strong> is a genuinely good visual programming environment. Routers, iterators, aggregators and its data-mapping panel handle branching flows well, and non-developers can read the result. Very large scenarios become hard to navigate, and anything the modules do not cover means reaching for HTTP modules and careful JSON handling.\u003C/p>\n\u003Cp>\u003Cstrong>n8n\u003C/strong> sits closest to code. It has branching, loops, sub-workflows, dedicated error workflows and code nodes where you write JavaScript or Python when the visual tools run out. For developers this is the main attraction: you never hit a wall where the only answer is "that's not possible in this tool."\u003C/p>\n\u003Ch2 id=\"section-5\">Integrations\u003C/h2>\n\u003Cp>Zapier has the largest integration library by a wide margin, with thousands of apps. If your stack is a long tail of niche SaaS tools, Zapier probably has all of them.\u003C/p>\n\u003Cp>Make has a large library that covers most mainstream tools.\u003C/p>\n\u003Cp>n8n has fewer native nodes, but its HTTP Request node and community nodes connect to anything with an API. In our experience, the missing native integration is rarely the blocker. Understanding the other system's API is, and that work is the same in every tool.\u003C/p>\n\u003Ch2 id=\"section-6\">AI features\u003C/h2>\n\u003Cp>All three now offer AI steps, and all three can call models from OpenAI, Anthropic and Google.\u003C/p>\n\u003Cp>n8n goes furthest for building AI systems rather than adding one AI step. It has agent nodes that call tools, conversation memory, vector store integrations for retrieval-augmented generation, and the freedom to mix those with ordinary logic and code. In our \u003Ca href=\"/projects/custom-rag-assistants\">custom RAG assistants\u003C/a> and the AI layer of \u003Ca href=\"/projects/hashtpa-ai\">Hashtpa\u003C/a>, n8n handles orchestration, queues and retries around model calls.\u003C/p>\n\u003Cp>If you only need "summarize this email" or "classify this ticket" as one step in a flow, Zapier's and Make's AI steps are perfectly adequate.\u003C/p>\n\u003Ch2 id=\"section-7\">When each one is the wrong choice\u003C/h2>\n\u003Cul>\n\u003Cli>\u003Cstrong>Zapier is the wrong choice\u003C/strong> for high-volume flows, workflows that loop over lists, or anything that needs real error handling. The bill and the workarounds both grow faster than the value.\u003C/li>\n\u003Cli>\u003Cstrong>Make is the wrong choice\u003C/strong> when data must stay in your infrastructure, or when a scenario has grown so large that nobody on the team can safely change it.\u003C/li>\n\u003Cli>\u003Cstrong>n8n is the wrong choice\u003C/strong> when nobody can own a server and the automation is small. Use n8n Cloud, or use Zapier and move on.\u003C/li>\n\u003C/ul>\n\u003Ch2 id=\"section-8\">How we choose on client projects\u003C/h2>\n\u003Cp>We ask four questions:\u003C/p>\n\u003Col>\n\u003Cli>\u003Cstrong>How many runs a month, and how many steps per run?\u003C/strong> That decides the cost curve.\u003C/li>\n\u003Cli>\u003Cstrong>Where does the data need to live?\u003C/strong> That can rule out SaaS on its own.\u003C/li>\n\u003Cli>\u003Cstrong>Who maintains it after launch?\u003C/strong> A marketing team that owns its own automations may be happier in Zapier or Make than in a more powerful tool they cannot change.\u003C/li>\n\u003Cli>\u003Cstrong>Is AI or custom code at the core, or on the edge?\u003C/strong> At the core, n8n.\u003C/li>\n\u003C/ol>\n\u003Cp>Most of our production automation runs on self-hosted n8n. In the \u003Ca href=\"/projects/mailflow-campaign-suite\">MailFlow campaign suite\u003C/a>, launching a campaign starts an n8n flow that sends, waits, checks opens and queues follow-ups to people who did not open. In our \u003Ca href=\"/projects/price-monitor-panel\">price monitoring panel\u003C/a>, n8n schedules the crawlers, retries failures and sends alerts. We still build in Zapier and Make when the client's team will own the flows and the volume is modest.\u003C/p>\n\u003Ch2 id=\"section-9\">Migrating between them\u003C/h2>\n\u003Cp>Moving from Zapier or Make to n8n is common once volume grows. A few lessons:\u003C/p>\n\u003Cul>\n\u003Cli>\u003Cstrong>Rebuild, don't translate.\u003C/strong> Map what each flow does in business terms, then build it the way n8n works best. A literal step-by-step copy carries over the old tool's workarounds.\u003C/li>\n\u003Cli>\u003Cstrong>Run both in parallel\u003C/strong> for a week and compare outputs before switching off the old flow.\u003C/li>\n\u003Cli>\u003Cstrong>Move the expensive flows first.\u003C/strong> The high-volume flows drive both the bill and the benefit of switching.\u003C/li>\n\u003C/ul>\n\u003Cp>If you want help choosing or migrating, see our \u003Ca href=\"/services/ai-automation\">automation and AI service\u003C/a>. We usually have the first flow running on your real accounts within the first week.\u003C/p>\n",[6,9,12,15,18,21,24,27,30],{"id":7,"text":8},"section-1","The comparison at a glance",{"id":10,"text":11},"section-2","Pricing models decide more than features",{"id":13,"text":14},"section-3","Hosting and data control",{"id":16,"text":17},"section-4","Complexity and custom logic",{"id":19,"text":20},"section-5","Integrations",{"id":22,"text":23},"section-6","AI features",{"id":25,"text":26},"section-7","When each one is the wrong choice",{"id":28,"text":29},"section-8","How we choose on client projects",{"id":31,"text":32},"section-9","Migrating between them",[34,37,40,43,46],{"q":35,"a":36},"Is n8n cheaper than Zapier?","For small, simple workflows the difference is minor. For long or high-volume workflows, n8n is usually much cheaper: n8n Cloud charges per execution rather than per step, and self-hosted n8n costs only the server it runs on.",{"q":38,"a":39},"Can non-developers use n8n?","Yes, for straightforward workflows. The interface is visual and many flows need no code at all. n8n rewards some comfort with JSON and APIs more than Zapier does, so a non-technical team may find Zapier or Make easier to own.",{"q":41,"a":42},"Is self-hosted n8n really free?","The community edition can be self-hosted without license fees for use inside your own business. Its license restricts offering n8n itself as a service to others. You still pay for the server and for the time to maintain it.",{"q":44,"a":45},"Which platform is best for AI agents?","n8n offers the most control for AI systems: agent nodes with tools and memory, vector store integrations for retrieval, and code wherever you need it. Zapier and Make are fine when AI is a single step inside a larger flow.",{"q":47,"a":48},"Can we move our Zaps or Make scenarios to n8n?","Yes, but plan it as a rebuild rather than a copy. Document what each flow does, rebuild it in n8n, run old and new in parallel, and switch over once the outputs match.","Frequently asked questions",1431,1790485335179]