
Magento
E-commerce Platform
Medusa
E-commerce PlatformMagento and Medusa are both popular choices, but they serve different needs. Magento is a E-commerce Platform with a traditional, manual approach to building, while Medusa is a E-commerce Platform that prioritises developer or designer control.
Below you'll find a side-by-side breakdown of detection signals, AI scores, and technical fingerprints — plus our honest take on which builder wins for different use cases.
How we detect Magento vs Medusa — see our methodology: AI Influence Score calculation, evidence tiers, and fingerprint signal types.
| Category | E-commerce Platform | E-commerce Platform |
| AI Score | 20/100 — Traditional | 20/100 — Traditional |
| Detection Signals | 8 patterns | 2 patterns |
| Script Detection | 3 patterns | — |
| CDN Detection | — | — |
| Header Detection | 1 headers | 1 headers |
| Sites Detected | 51 scans | No data yet |
| Best For | Online stores & product catalogsTry Magento → | Online stores & product catalogs |
| Official Website | Visit | — |
E-commerce Platform
Magento is a e-commerce platform with an AI Score of 20/100 (Traditional). Our detection engine uses 8 signal patterns to identify Magento-built sites.
E-commerce Platform
Medusa is a e-commerce platform with an AI Score of 20/100 (Traditional). Our detection engine uses 2 signal patterns to identify Medusa-built sites.
Magento is an open-source e-commerce platform owned by Adobe, widely adopted by mid-market and enterprise retailers who require flexible product catalog management, multi-store configurations, and robust checkout workflows. The AIWebsiteDetector.com engine identifies Magento deployments through a combination of 3 script patterns, 3 HTML patterns, 1 HTTP header, and 1 meta tag pattern, collectively targeting signals such as Magento-specific JavaScript bundles, inline HTML attributes tied to its templating architecture, and server-response headers that surface the platform's identity. These layered detection signals allow the tool to distinguish between Magento 1.x legacy installations and Magento 2.x (Adobe Commerce) deployments, since each generation leaves meaningfully different fingerprints across page source and network responses. Magento sites are commonly hosted on dedicated cloud infrastructure, including Adobe Commerce Cloud, as well as third-party managed hosting providers optimized for PHP-based workloads, making hosting environment alone an unreliable sole indicator — which is precisely why multi-signal detection is necessary. The platform's official home is at [https://business.adobe.com/products/magento](https://business.adobe.com/products/magento), and its prevalence across large-scale retail and B2B commerce sites makes accurate detection particularly valuable for competitive analysis, technology auditing, and security research.
Medusa is an open-source, headless e-commerce platform built for developers and digital commerce teams who need a highly customizable alternative to traditional monolithic storefront solutions. Designed with a modular architecture, Medusa is commonly deployed by technical teams building custom storefronts, multi-region shops, and composable commerce experiences using its Node.js-based backend. AIWebsiteDetector's detection engine identifies Medusa-powered sites using a combination of one distinct HTML pattern and one HTTP header signature that are consistently present across Medusa deployments. These signals reflect Medusa's characteristic server responses and frontend markup conventions, allowing the detection engine to distinguish it reliably from other headless or API-first commerce frameworks. Because Medusa is self-hosted and open-source with no mandatory licensing fees, its deployments vary widely in infrastructure — ranging from cloud platforms like Railway and Render to custom VPS setups — but the core fingerprint remains consistent enough to support confident identification.
Choose Magento if…
Choose Medusa if…
Our Pick — Based on 51+ detections
The most frequently detected e-commerce platform in our scan database.
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