Modern frontend applications are getting bigger and bigger. It is no wonder that the industry is getting more concerned with optimizations. Frameworks create unreasonable build sizes for applications that can either make or break your application. Every unnecessary bit of JavaScript code you bundle and serve will be more code the client has to load and process. The rule of thumb is the less, the better.
Data loading patterns are an essential part of your application as they will determine which parts of your application are directly usable by visitors. Don’t be the site that slows their entire site because they chose to load a 5MB image on the application’s homepage and understand the issue better. You need to know about the resource loading waterfall.
The resource loading waterfall is a cascade of files downloaded from the network server to the client to load your website from start to finish. It essentially describes the lifetime of each file you download to load your page from the network.
You can see this by opening your browser and looking in the Networking tab.
What do you see there? There are two essential components that you should see:
No one likes a white blank screen, especially your users. Lagging resource loading waterfalls need a basic placeholder before you can start building the layout on the client side. Usually, you would use either a spinner or a skeleton loader. As the data loads one by one, the page will show a loader until all the components are ready.
While adding loaders as placeholders is an improvement, having it on too long can cause a “spinner hell.” Essentially, your app is stuck on loading, and while it is better than a blank HTML page, it could get annoying, and visitors would choose to exit your site.
But isn’t waiting for the data the point?
Well, yes, but you can load it faster.
Assuming you want to load a social media layout, you might add a loading spinner or a skeleton loader to ensure that you don’t load an incomplete site. The skeleton loader will usually wait for:
You make an asynchronous call to an API, after which you get the URL for the asset on the CDN. Only then can you start building the layout on the client side. That’s a lot of work to show your face, name, status, and Instagram posts on the first try.
Developing software is becoming easier as frameworks like React, Vue, or Angular become the go-to solution for creating even the simplest applications. But using these bulky frameworks filled with a ton of magical functions you don’t even use isn’t what you should be going for.
You’re here to optimize. Remember, the less, the better.
But what if you can’t do less? How will you serve blazingly fast code, then? Well, it’s good that you’re about to learn five data-loading patterns that you can use to get your site to load quickly or, as you would say, blazingly fast.
Server-side rendering (SSR) is when an application serves plain HTML to the client. SSR can be divided into two types: SSR with hydration and SSR without hydration. SSR is an old technique used by older frameworks such as WordPress, Ruby on Rails, and ASP.NET. The main goal of SSR is to give the user a static HTML with the prerequisite data. Unlike CSR, SSR doesn’t need to make another API call to the backend because the server generates an HTML template and loads any data within it.
Newer solutions like Next.js uses hydration, where the static HTML will be hydrated on the client side using JavaScript. Think of it like instant coffee, the coffee powder is the HTML, and the water is the JavaScript. What happens when you mix instant coffee powder with water? You get — wait for it — coffee.
But what is a Jamstack? Jamstack is similar to SSR because the client retrieves plain HTML. But during SSR, the client retrieves the HTML from the server. However, Jamstack apps serve pre-generated HTML directly from the CDN. Because of this, Jamstack apps usually load faster, but it’s harder for developers to make dynamic content. Jamstack apps are good with pre-generating HTML for the client, but when you use heavy amounts of JavaScript on the client side, it becomes increasingly harder to justify using Jamstack compared to Client Side Rendering (CSR).
Both SSR and Jamstack have their own differences. What they do have in common is they don’t burden the client with rendering the entire page from scratch using JavaScript.
When you optimize your site’s SEO, using SSR and Jamstack are recommended because, compared to CSR, both return HTML files that search bots can easily traverse. But search bots can still traverse and compile JavaScript files for CSR. However, rendering every JavaScript file in a CSR app can be time-consuming and make your site’s SEO less effective.
An SSR application will generally have templating engines that inject the variables into an HTML when given to the client. For example, in Next.js, you can load a student list writing:
Jamstack is popular with documentation sites that usually compile code to HTML files and host them on the CDN. Jamstack files usually use Markdown before being compiled to HTML, for example:
When you want to get data that you already had quickly, you need to do caching — caching stores data that a user recently retrieved. You can implement caching in two ways: using a super-fast key-value store like Redis to save data keys and values for you and using a simple browser cache to store your data locally.
Caching partially stores your data and is not used as permanent storage. Using the cache as permanent storage is an anti-pattern. Caching is highly recommended for production applications; new applications will start using caches as they gradually mature.
But when should you choose between a Redis cache (server cache) and a browser cache (local cache)? Both can be used simultaneously but will ultimately serve a different purpose.
Server caches help lower the latency between a Frontend and Backend; since key-value databases are faster than traditional relational SQL databases, it will significantly increase an API’s response time. However, a local cache helps improve app state management, enabling the app to persist state after a page refresh, and helps future visits.
You can make a real-time live connection between the Front-end and Backend via WebSockets. WebSockets are a two-way communication mechanism that relies on events.
In a common WebSocket architecture, the Front-end application will connect to a WebSocket API, an event bus, or a database. Most WebSocket architectures utilize it as a substitute to REST, especially in use cases like chat applications; polling your Backend service every few seconds becomes a very inefficient solution. WebSockets allow you to receive updates from the other end without needing to create a new request via the two-way connection.
A pure WebSocket implementation still has a lot of faults. Using WebSockets instead of regular HTTP calls changes how your entire application behaves. Just a slight connection issue can affect your overall UX. For example, a WebSocket cannot have real-time performance when it needs to query the database every time there is a get request. There are bottlenecks in the backend that needs to be optimized for better real-time results to make WebSockets feasible and a more reasonable answer.
Modern JavaScript has WebSocket providers that you can use. The WebSocket class opens a connection to a remote server and enables you to listen when the WebSocket opens a connection, closes a connection, returns an error, or returns an event:
Do you want to react to server events? Add an addEventListener function and insert a callback that it will use:
Prefetching and lazy loading has become common knowledge among frontend developers. Efficient use of a client’s resources and bandwidth can greatly improve your application’s performance.
You specify prefetch URLs within the link HTML element, more specifically, the rel attribute. Prefetching has a few pros and cons:
Lazy loading is a common data-loading pattern that makes the client load à la carte results, not loading everything until the client needs it. Lazy loading will make the client fetch the latter parts of a website after they’ve scrolled into view.
Lazy loading makes your site load faster by allowing the browser to concentrate on more important, on-screen resources. You won’t need to load all the images/text on a given site when you can’t see it. But lazy loading can only help you delay downloading resources and doesn’t make your resources smaller and more cost-efficient.
However, if you are looking to make a more cost-efficient solution that is similar to lazy loading, try looking for Resumability.
The main idea of Resumability is to serialize the application state from the server to the client. Instead of loading everything (HTML, JS) and hydrating them on the Front-end, Resumability serializes the JavaScript parsing in stages and sends them to the client in HTML.
Page startups will be instantaneous because the client doesn’t have to reload anything and can deserialize the state injected into the HTML. Resumability is a very foreign concept and is not common in many projects. It was coined by the founder of Qwik, Misko Hevery.
The root has a dependency on App. It will be the lazy loaded Qwik component:
Qwik and React have similarities at the component level. But it differentiates when you get into the server side of things.
The code snippet above shows you how the server-side of Qwik serializes the root component using the renderToString method. The client will then only need to parse pure HTML and deserialize the JavaScript state without needing to reload them.
Application performance is essential for the client. The more resources you have to load on startup, the more time your app will need to bootstrap. Loading times expectations are getting lower and lower. The less time you need to load a site, the better.
But if you are working on large enterprise applications, how you can optimize your apps are not obvious. Data-loading patterns are one way you can optimize your applications’ speed. In this article, you reviewed five data-loading patterns that may be of use:
All five of which are useful in their own circumstances.
SSR and Jamstack are generally good choices for applications that require less client-side state management. With the advent of modern JavaScript frameworks like React, more people have tried Client Side Rendering (CSR), and it seems that the community has come full circle back to SSR. SSR is the technique used by old MVC web frameworks to use template engines to generate HTML based on the data on the backend. Jamstack is an even older depiction of the original web, where everything was using just HTML.
Active memory caching helps users load data from APIs faster. Active memory caching solves the important issues around data loading by either caching the results on a remote cache server (Redis) or your local browser cache. Another data-loading pattern even uses it, prefetching.
Next, event sourcing is an architectural pattern that supplements the real-time event-based WebSocket APIs. Plain old WebSockets are not enough to become completely efficient because even though the WebSocket itself is real-time, the recurring API call to the database can cause a bottleneck. Event sourcing removes this problem by creating a separate database for retrieving data.
Prefetching and lazy loading are the easiest solutions to implement. The goal of prefetching is to load data silently during network idle times. Clients will save the prefetched link inside their browser caches, making it instantaneous on contact.
Lazy loading reduces the number of resources you need to load on the first click. You only need the resources that you see directly after the page loads. However, Resumability takes lazy loading to the extreme. Resumability is a method of lazy loading JavaScript components by rendering them in the server and then serializing the state to continue the render on the client via HTML.
Learning to optimize your Frontend applications is an ongoing process; you need to be proactive about what you implement daily. Data-loading patterns are only one of a few ways you can use to improve your application performance.
But it is best to consider the common pitfalls before making any drastic changes to how your application is structured and consumes and loads data.
If you’re interested in exploring the references, you can check out:
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