Zapier vs Make vs n8n: Best Automation Platform Compared

Workflow automation has become infrastructure for modern businesses. Whether you are connecting a form submission to a CRM, syncing data between SaaS apps, or orchestrating complex multi-step processes, the platform you choose shapes what is possible and what it costs. Zapier, Make (formerly Integromat), and n8n are the three platforms that consistently appear in buying decisions.

This comparison draws from building and maintaining automations across all three platforms — from simple two-step zaps to complex workflows processing thousands of records daily.

Platform Overview

Pricing

Pricing is where these platforms diverge most sharply. Zapier is the most expensive by a significant margin, particularly at scale. A workflow with 5 steps that runs 1,000 times costs 5,000 tasks on Zapier but 5,000 operations on Make and 1,000 executions on n8n. At high volumes, Make is roughly 3-5x cheaper than Zapier, and self-hosted n8n is cheaper still.

The billing unit matters more than the sticker price. Zapier counts every action step as a task. Make counts every module execution as an operation. n8n counts each complete workflow run as one execution regardless of how many nodes it contains. For multi-step workflows, n8n's model is the most cost-effective.

Ease of Use

Zapier is the easiest to learn. Its linear, step-by-step builder (trigger → action → action) maps to how most people think about automation. You pick an app, choose a trigger, pick another app, choose an action, map fields, and turn it on. A non-technical team member can build a working automation in under ten minutes. The trade-off is that complex logic — branching, loops, error handling — requires workarounds or premium features.

Make uses a visual canvas where you drag modules and connect them with lines. This is more powerful than Zapier's linear model because you can see branches, parallel paths, and error routes spatially. The learning curve is steeper — understanding how data flows through routers, iterators, and aggregators takes practice — but the visual feedback makes complex workflows easier to understand and debug once you learn the model.

n8n's interface is similar to Make's — a canvas with nodes and connections. The key difference is that n8n expects more technical comfort. Expressions use JavaScript syntax. Debugging shows raw JSON data. The self-hosted version requires you to manage infrastructure. For developers and technical ops teams, this is a feature. For marketing teams building lead routing, it can be a barrier.

Integration Ecosystem

Zapier's 7,000+ app integrations is its strongest moat. If a SaaS product has an API, it probably has a Zapier integration. Many SaaS companies build Zapier integrations before building their own API docs because that's where their users expect to connect things. For teams using niche tools, Zapier is often the only option with a pre-built connector.

Make offers around 1,800 integrations, which covers all major SaaS tools and many mid-tier ones. Where Make falls behind Zapier in breadth, it often surpasses it in depth — Make's modules for tools like Google Sheets, Airtable, and Shopify expose more API endpoints and offer finer control than Zapier's equivalent actions.

n8n has 400+ built-in integrations and a growing community-contributed library. The practical gap is smaller than the numbers suggest because n8n's HTTP Request node and Code node let you connect to any API directly. If you are comfortable reading API documentation and writing a few lines of JavaScript, n8n can integrate with anything. If you want point-and-click setup for a niche tool, Zapier is the safer bet.

Complex Workflow Capabilities

As workflows get more complex, the gap between these tools widens.

Zapier handles simple to moderate workflows well. Paths (branching) and Looping are available on Professional plans and above. Filters let you conditionally continue or stop a workflow. For most "if this then that" automations, Zapier is sufficient. Where it struggles is with data transformation — reformatting dates, restructuring JSON, aggregating data from multiple sources — which often requires Formatter steps or Code steps.

Make was designed for complex workflows. Routers split data into parallel branches. Iterators process arrays item by item. Aggregators combine results. Error routes let you define exactly what happens when a step fails — retry, send an alert, route to a fallback. The visual canvas makes it possible to build and maintain workflows with 20-30 modules that would be nearly impossible to follow in Zapier's linear view.

n8n matches Make in complexity handling and adds two significant capabilities: sub-workflows and full code nodes. Sub-workflows let you compose large automations from reusable pieces, similar to functions in programming. Code nodes accept arbitrary JavaScript or Python, meaning there is no data transformation you cannot do. For engineering teams, n8n effectively eliminates the ceiling on what is possible within a workflow.

Self-Hosting and Data Control

This is n8n's unique advantage. You can run n8n on your own infrastructure — a Docker container, a Kubernetes cluster, or a simple VPS. Your workflow data, credentials, and execution logs never leave your servers. For companies in regulated industries (healthcare, finance, government), or teams that simply prefer data sovereignty, self-hosting is the deciding factor.

Neither Zapier nor Make offer self-hosting. All data, credentials, and execution logs live on their cloud infrastructure. Both comply with SOC 2 and GDPR, but if your security policy requires on-premises data processing, they are not options.

Self-hosting n8n does come with operational overhead. You manage updates, backups, scaling, and uptime. n8n's cloud offering eliminates this overhead while maintaining the same feature set, though you trade data sovereignty for convenience.

AI and LLM Integration

All three platforms have added AI capabilities, reflecting the demand for LLM-powered automations.

Zapier offers AI actions that connect to OpenAI, Anthropic, and other providers. Its chatbot builder lets you create AI assistants that pull data from connected apps. The implementation is straightforward — add an AI step like any other action — but the depth is limited to what Zapier's interface exposes.

Make provides AI modules for major LLM providers with configurable parameters (temperature, max tokens, system prompts). Chaining AI modules with data processing modules enables more sophisticated AI workflows, like processing a batch of support tickets through an LLM and routing them based on the response.

n8n's AI integration is the deepest. It includes a LangChain integration that supports agents, chains, memory, and tool use. You can build AI agents that call external tools, maintain conversation context, and make decisions within a workflow. For teams building production AI automations rather than simple prompt-and-response chains, n8n offers the most control.