#NextJS 🛟 : How Companies Optimize Caching for Scalability

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🌟 Introduction

Caching is a powerful technique for improving web performance and scalability in the context of modern web development. It reduces server load, speeds up content delivery, and ensures a better and smoother user experience.

Choosing the right caching strategy can be challenging, especially for high-traffic applications that require a balance between speed and data freshness.

🔄 Understanding Caching Strategies in Modern Web Apps

Before diving into case studies, let’s quickly cover the key caching strategies:

• Server-side caching: Using Next.js features like Incremental Static Regeneration (ISR) and Server-Side Rendering (SSR) to control data freshness.
• Client-side caching: Leveraging browser cache and Service Workers for faster repeat visits.
• CDN caching: Storing static assets and API responses at edge locations for reduced latency.

🚀 Real-world use cases:

We’ll look at real-world use cases from companies such as Vercel and Airbnb in order to see how they optimize caching to handle millions of users efficiently. Even though, the second company mentioned is not necessarily using Next.js for its main platform, we will look at its caching strategy as an inspiration for future Next.js applications.

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🎯 Case 1: Vercel - How Vercel optimizes caching for deployments and previews

🔍 Problem

Vercel hosts thousands of Next.js applications, needing:

• Fast build times for developers deploying changes.
• Efficient caching for assets and API responses.
• Edge delivery to ensure global performance.

🔧 Solution

Vercel uses:

• ISR (revalidate) to enable dynamic content updates without rebuilding everything.
• CDN edge caching for pre-rendered pages and assets.
• Serverless functions (cache: 'no-store') to avoid stale API data.

✅ Outcome

• Faster deployments with instant cache invalidation.
• Lower backend load since static pages are cached globally.
• Optimized performance for dynamic and static sites.

🔑 Key Takeaway: Next.js with ISR and CDN caching enables fast updates while reducing backend stress.

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🎯 Case 2: Airbnb - Ensuring Fresh Data for Real-Time Booking

🔍 Problem

Airbnb listings change in real time, and stale data can cause:

• Double bookings when availability isn’t updated fast enough.
• Delayed search results, frustrating users.
• High backend traffic from constant API calls.

🔧 Solution

Airbnb optimized caching by using:

• SSR (cache: 'no-store') → Ensures real-time availability updates.
• Static caching (force-cache) for listing details and images.
• CDN caching to distribute static assets globally.

✅ Outcome

• Reduced booking conflicts.
• Faster response times globally.
• More scalable backend, as only dynamic data hits the server.

🔑 Key Takeaway: When real-time accuracy is critical, SSR + selective static caching is the best approach.

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🌟 Takeaways for your future Next.js App

The best caching strategy depends on your data:

• For frequently updated but non-critical data (like blog posts) → Use ISR (revalidate) + CDN caching.
• For real-time updates that must be fresh (like transactions) → Use SSR (cache: 'no-store').
• For static content (like images, assets) → Use force-cache + long TTLs.

Mixing these strategies ensures better performance, lower costs, and higher scalability.

Until next time 👋,

Stefania

P.S. Don’t forget to like, comment, and share with others if you found this helpful!

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💬 Let’s talk:

What caching strategy does your app use?

Let’s discuss in the comments! 🚀

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