🚅 Frontend API calls optimization: Caching vs Pagination
Why should you use caching instead of pagination when optimizing Frontend API calls ? | ♻️ Knowledge seeks community #6 | 🚅 Performance Optimization
Hi,
Hope you’re having a great day 🤗!
This is a brief note regarding a question I encountered while working on one of my side projects. I believe its answers provide valuable insights into frontend performance optimization.
So, let’s dive in 👩🚀.
Why should you use caching instead of pagination when optimizing Frontend API calls ?
When optimizing frontend API calls, caching and pagination are both useful techniques, but they serve different purposes. Here's why caching might be the better option in certain situations:
1. Reduced Load on Backend
Caching can store the data that has already been retrieved and serve it directly to users without making additional API calls. This reduces the number of requests made to the backend and lessens server load, making your application more efficient.
Pagination, while useful for large datasets, still requires multiple requests to the backend as the user navigates through pages, especially if they want to load a larger dataset. Caching helps avoid repetitive requests for the same data.
2. Faster Data Access
Caching ensures that the data is readily available in the client or on an intermediary cache layer (e.g., CDN or browser cache), which results in faster response times since the data doesn’t need to be fetched from the server repeatedly.
Pagination is typically slower when you're fetching new data from the server as the user interacts with the UI, especially when dealing with large datasets. Each new page load could involve network latency.
3. Better User Experience
Caching can provide a smooth user experience, especially when the same data is needed frequently (e.g., lists, user profiles). The data appears instantly as it is already stored, preventing delays in rendering the UI.
Pagination introduces delays with each new page load and can sometimes create a fragmented or frustrating user experience, especially in cases where users expect seamless interaction.
4. Reduced Server Bandwidth
Caching can significantly reduce bandwidth usage by preventing redundant API calls. If data doesn’t change frequently, caching ensures that the same request isn’t sent to the server multiple times.
Pagination can still result in multiple API calls for the same dataset as the user navigates through pages, increasing the server's bandwidth usage.
5. Handling Large Datasets Efficiently
Caching is particularly useful for large datasets that don’t change often, allowing the frontend to store a snapshot of the data. This way, pagination is unnecessary, as you can store the entire result set and render it on the frontend as needed.
Pagination is suited for large datasets that change frequently, but it can be a performance bottleneck when users need to access a lot of data quickly or in multiple sessions.
6. Better for Data That Doesn't Change Often
Caching is ideal when the data is relatively static and doesn’t change frequently (e.g., reference data, settings, or non-time-sensitive data). This allows the frontend to rely on cached data for repeated views.
Pagination is more useful for dynamic datasets that change over time (e.g., user-generated content), as it helps avoid overwhelming the client with too much data at once.
When to Combine Caching and Pagination:
You can combine both techniques (hybrid approach), especially when dealing with large datasets and static data that doesn’t change often. Use pagination to load smaller chunks of data and cache those chunks when appropriate.
Let’s take the following example where an hybrid approach would work:
A Product Listing Page in an E-commerce App - Imagine building an e-commerce site with a product listing page that includes various filters, sorting options, and pagination. We could have the following flow:
User visits the e-commerce site and views the Electronics category.
The app makes an API call to fetch products for the "Electronics" category, caches the response.
The products are displayed with pagination (10 products per page).
User navigates to page 2 of the list.
The app checks if page 2 is cached for the "Electronics" filter.
If cached, it serves the data from the cache.
If not cached, it fetches the data from the backend, then caches the response.
User sorts the list by price from low to high.
The app checks if the sorted list is cached.
If cached, it serves the sorted list from the cache (either page 1 or a new page if it hasn't been paginated yet).
If not cached, it fetches the sorted list and stores it in the cache for future use.
In this case the benefits of using an hybrid approach would be:
Efficiency - only necessary data is fetched from the server and if the user goes back to an old filtering and sorting option, the cached data will be used.
Performance - users sees immediate results from cached data, while the pagination ensures that the page doesn’t freeze while waiting for data to load.
Backend load reduction - the server is only called when the cached data gets invalidated or the data requested is not cached.
Improved user experience - If the user changes filters or sorting, the app doesn't need to reload everything from scratch. If the cache is still valid, the user sees the results immediately; otherwise, a fresh request is made.
To conclude:
Use caching when the data is static, doesn’t change often, and is accessed frequently (to reduce server load and improve performance).
Use pagination when you're dealing with large, dynamic datasets that users need to interact with piece by piece for a better experience.
For optimal performance, combine caching and pagination when you need both approaches to address different aspects of the API calls.
This decision should always be based on your data structure, user experience goals, and the specific behavior of your application.
Until next time 👋,
Stefania
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