What Is Caching? How It Works, Types, and Best Practices

Caching is like having your groceries pre-ordered based on your transaction history. Instead of roaming different aisles to find your items, the store pre-stocks your commonly purchased goods for immediate checkout.

When you use a computer or browse the internet, caching stores information that you use frequently. This way, your device can quickly grab that information from the cache instead of fetching it from the main storage every time it’s needed.

In modern computing, caching is used to make a computer, browser, or application run faster. Similarly, caching helps online services and devices deliver a smoother, quicker user experience. It achieves this objective by reducing the distance data travels and avoiding the need to process the same data repeatedly.

Caching is one of the most important technologies in fields that require data computing. Here’s a more detailed breakdown of how this technology works and its importance.

The Core Concept: Storing Frequently Accessed Data

We use caching technology to store in an easily accessible location data your system frequently needs. Because the system already knows what you’re looking for based on your activity, it stores this information in a location it can easily access. As a result, the data doesn’t need to travel as far to get to the user.

Upon user request, the system can simply fetch the file from a closer, secondary location. When that happens, your applications or websites will run faster and more efficiently since caching reduces page load times.

Purpose: Improving Performance and Reducing Latency

One reason caching is such an important piece of web technology is that it improves performance. As we discussed earlier, this technology reduces the time it takes to access data, also known as latency.

By storing frequently accessed information in the cache, systems can quickly retrieve this data when needed. This improved accessibility also results in a better user experience.

The History of Caching in Computing

Caching in cloud computing has a pretty interesting history. In 1965, British computer scientist Maurice Wilkes introduced this technology, but it had a rather controversial name: “slave memory.”

Two years later, an IBM Systems Journal editor used the word “cache” to describe the new memory in IBM’s Model 85 computer. The phrase originated from the French word “cacher,” which means “to hide.”

The word “cache” soon became the standard usage in computing literature.

By now, you already know that caching speeds up the data-fetching process. But you probably don’t know that many processes occur in the background to make caching possible. Let’s take a quick look at these processes.

The Caching Process

Here are the five stages of the caching process and what they entail:

• Request for data: The system, such as a computer, website, or application, requests data from a specific resource.
• Checking the cache: The system then checks the cache to see if there’s a copy of this data from a previous request.
• Cache hit vs. cache miss: If the system finds the requested data in the cache, that’s what we call a “cache hit.” The opposite is pretty self-explanatory; if it can’t find the data from that particular resource, then that’s a “cache miss.” Next, the system attempts to retrieve the data from the original data source.
• Retrieving data from cache or source: Assuming we have a cache hit, the data loads from the cache. This process is quicker since data is readily available. On the other hand, when there’s a cache miss, the data travels all the way from its source to the requesting party, which takes longer.
• Updating cache, if necessary: When the system returns with fresh data from its source, it adds it to the cache for faster access in future requests. This system works best in situations where there’s a high chance the user will request the data in question again soon.

Learning about the caching process gives you a better understanding of how it speeds up data retrieval.

Caching is a versatile technology used across various platforms, many of which you interact with daily. Let’s discuss the three most common examples of caching technology in action.

Web Browser Caching

When you browse the internet, your web browser uses caching to store copies of web pages, images, and other content you’ve accessed.

This means the next time you visit the same website, your browser can load it faster because it retrieves much of the data from its cache and cookies rather than downloading everything from the web server again.

Database Caching

The same process applies to some database systems. When you or an application makes a repeat query, the database can quickly return the stored result instead of heading to the database storage to locate the data and then feed it to the user.

This process speeds up data access and works best in environments with high read and query volumes, such as an eCommerce website during peak shopping seasons.

Content Delivery Networks (CDNs)

Content delivery networks, such as CacheFly, use caching to speed up data delivery worldwide. They store cached content in multiple geographical locations close to users.

For example, if you run a website or application targeting the Brazilian market, you need a web host with CDNs near Brazil.

This means that when you access a video, image, or webpage, the system will retrieve it from the copies saved in the nearest location. As you’d expect, fetching data from the nearest location also means faster delivery to whoever requested it.

Caching doesn’t happen only at the browser level. Below, we’ll explore different types of caching technologies and their environments.

Client-Side Caching

This type of caching stores files locally, eliminating the need to repeatedly remove them. Caching on the client’s side falls into two categories: browser and mobile app caching.

Browser Caching: When you visit a website, your browser stores certain elements like images, HTML, CSS, and JavaScript files. When you revisit the site, the browser loads it from the local cache rather than downloading everything from the server again.

Mobile app caching: Like browser caching, mobile applications cache data to avoid downloading it every time you use the app.

For most browsers, you can easily clear your cache by going to Menu > Settings > Clear browsing data. Depending on your browser, you might see Preferences or Tools instead of Settings.

Server-Side Caching

This type of caching happens on the server that hosts websites or applications. Here, you’ll find two types of caching technologies: database and application-level caching.

Database caching: As the name implies, this type of caching temporarily stores frequently accessed data, such as query results or common requests. Remember, the primary goal of any caching process, regardless of where it happens, is to access data faster without loading it from the original source.

Application-level caching: When caching takes place at the application level, it stores parts of dynamically generated web pages or other outputs from an application to serve them quickly on future requests.

For instance, when there’s a viral news topic, like a major sporting event, the application may store a rendered HTML version of this page in its cache after the first request. Subsequent visitors will then receive the cached version. This guarantees a seamless reading experience even under high demand.

Distributed Caching

Distributed caching distributes data to a network of cache servers, hence the name. This process allows multiple users in different locations to access the cached content quickly. Under distributed caching, you’ll find two caching technologies:

Content delivery networks: CDNs deliver internet content, including webpages, videos, and images, faster by caching the content in different geographical locations closer to users. It includes the entire system of distributed servers that work together to speed up content delivery to the user.

Edge caching: On the other hand, this type of caching is part of a CDN strategy that involves caching data at the network’s edge. This means the caching process takes place closer to the user to reduce latency.

In-Memory Caching (Object Caching)

This caching technology is extremely fast because it reads data from memory, not the disk. Think about a topic you’re an expert in. You can likely recite dozens of facts from memory more quickly than someone unfamiliar with the subject who would need to look it up. In-memory caching comes in two versions:

Redis: This is an open-source, in-memory data structure store used as a database, cache, and message broker. Redis supports various data structures such as strings, hashes, lists, and more, making it versatile for different caching needs.

Memcached: This is a high-performance, distributed memory object caching system mostly used to speed up dynamic web applications. It is usually more effective at caching small chunks of arbitrary data or the results of database and API calls.

As you can see, caching has one primary objective: to speed up the transfer of files from one point to another, whether on a mobile application, website, server, or even a browser.

That said, not every caching system you encounter will work for you. For instance, Memcached works best for dynamic web applications, such as Gmail or X (formerly Twitter), where you don’t need to reload the entire application to update the user interface.

On the other hand, database caching works best in an environment that mainly deals with databases. So, to find the right caching technology, you should first understand your unique needs.

Let’s take a more detailed look at the benefits of caching. This should help you understand why this technology is still relevant decades after its inception.

Improved performance and response times: As mentioned, caching speeds up data access by eliminating the need to fetch data directly from the server and then transfer it to the user. As a result, this technology leads to faster performance and quicker response times.

Reduced load on servers: Since there is no need to fetch data directly from its original location, caching reduces server load. Keep in mind that every time you send a request to the server, it has to run some processes in the background to retrieve whatever information you need; however, since the cache handles the bulk of data requests, the number of direct requests to the server for data retrieval decreases.

Enhanced scalability: Scalability is a little-known yet critical benefit of implementing caching technologies. The scalability comes from the fact that caching reduces the need for additional server capacity to manage increased demand. That means you can scale your operations more economically and effectively.

Better user experience: Research has shown that most people will abandon a website if it takes more than three seconds to load. On the other hand, most people are more likely to interact with digital platforms that offer faster load times, consistent performance, and reliable accessibility. The key lesson here is that caching leads to a better user experience.

These benefits make caching an essential part of modern computing. It’s also not a one-sided technology; it improves user experience for both the technical backend and the front end.

Implementing caching in your systems is not just about plugging it in and hoping everything works smoothly. It’s worth learning a thing or two about the best practices in caching if you want to maintain optimal performance and ensure data reliability. Here’s what you need to know:

Cache Invalidation Strategies

Effective cache invalidation ensures that the caching system you’ve implemented does not serve stale data. Since caching involves fetching saved data without needing to load it from its original location, ensuring that the data is up-to-date is important. To achieve this goal, you can either use time-based or event-based invalidation.

Time-based invalidation: Here, you set up an expiration time for data in the cache. Once the set time has elapsed, the data becomes stale and is either deleted or refreshed on the next request.

Event-based invalidation: This strategy invalidates cache entries immediately when an underlying data change event occurs. For example, suppose you’re offering a 50% discount on a product. Once you’ve updated the new price in the database, the update will instantly invalidate the related cache to prevent serving outdated information to users.

Despite the differences between these two methods, they all serve the same purpose: ensuring that the cache contains up-to-date and accurate information.

Cache-Control Headers

Cache-control headers manage how HTTP caches store and use your data.

In other words, they control the caching mechanisms of browser and intermediary caches, dictating how and for how long the caching process should last.

You’ll need to configure these headers properly to achieve better application performance and minimal server load.

For example, if you manage a news website that receives regular updates, you can update the Cache-control settings to “no-cache” to keep the content fresh whenever the user requests it.

Monitoring and Optimization

Don’t just set up caching technology and forget about it; you need to monitor it periodically to ensure everything runs as it should. You’ll likely need some tools to monitor performance and optimize cache usage.

Tools for monitoring cache performance: You have quite a number of options. You can opt for popular ones like Redis Monitor, Memcached Stats, and PerfMon, or even get yourself custom middleware. These tools help track hit rates, miss rates, and the efficiency of your caching layer.

Techniques for optimizing cache usage: Make sure the tools you use for cache monitoring support different optimization techniques, such as adjusting cache size, fine-tuning expiration policies, and using data compression for cache entries. Regularly reviewing and adjusting these parameters based on performance is also a great way to maintain an optimal setup.

Security Considerations

Without proper security systems in place, your cache data is at risk of breaches. Think about it this way — we’re talking about a copy of data stored away from the original source.

So, instead of trying to access the original storage location, all a malicious party needs to do is breach your cache. Let’s discuss some top security considerations to prevent this from happening.

Cache poisoning occurs when incorrect or malicious data gets stored in the cache, sometimes to spy on user activity and obtain important information that could infiltrate the entire system, including the server.

Cache poisoning can also lead to corrupted data being served to users. You should implement strict validation checks before data enters the cache to prevent this.

Data privacy concerns: You need to protect data by setting up encryption and authentication processes. This strategy prevents other parties from accessing private data without authorization.

In summary, you should think of cached files as copies of your private information that you wouldn’t want anyone to access without your permission. By following these best practices, you maximize the benefits of caching and minimize potential risks.

Caching is undoubtedly a powerful tool for enhancing system performance and user experience. But like any other technology, it also comes with its own set of challenges and limitations. Here are the most notable:

Cache Coherence Issues

Cache coherence refers to the challenge of keeping the data in the cache consistent with the data in the source or main storage. In other words, it’s about trying to make both sets of data agree with each other.

The most challenging part here is that you need to make sure that all caches are updated correctly when data changes. For instance, when you update a product’s price, you want the new price to reflect across all platforms immediately after running the update. Otherwise, users won’t trust your website or application.

The same applies to applications that handle live data. Let’s say you run a Forex trading platform that requires live updates. Of course, caching can help reduce server load and speed up data processing, but if there’s a cache coherence issue, users won’t instantly get the most up-to-date information as they should. That alone can be the difference between making profits or losses.

Cache Expiration and Staleness

Handling cache expiration and data staleness is an important aspect of caching, as we saw earlier. But despite its benefits, this process is also quite challenging when you have to decide how long data should remain in the cache before it’s considered outdated.

Any miscalculation at this stage can yield undesirable results. For instance, users might see outdated information, prompting them to lose trust in your application.

Over-Caching vs. Under-Caching

They say too much of a good thing is bad. The same concept applies to caching. You need to strike the right balance between over-caching and under-caching. Over-caching, which means storing too much cache, can lead to excessive memory use. Don’t forget that there’s also a risk of serving stale data if you practice over-caching.

Under-caching isn’t the solution to this problem either. In fact, it may not provide the intended performance benefits. The goal here is to find an optimal caching level by carefully studying usage patterns and data volatility.

Cache Size and Memory Constraints

Managing cache size and memory constraints is another potential challenge that comes with implementing this technology. An oversized cache can consume too much memory, affecting overall system performance and scalability.

On the other hand, if you opt for a cache that’s too small, you’ll have to deal with frequent cache misses, which defeats the whole point of having a cache in the first place. To fix this issue, you should adjust the cache size based on the available system resources and your application’s specific needs.

Quick tip: Remember that these are not the only challenges associated with implementing caching technology. You need a well-thought-out strategy and ongoing monitoring to prepare for anything further.

Caching technology is continuously evolving. What started as a simple memory upgrade by IBM in 1965 has become an important component of digital computing, especially where the internet is involved.

We now see newer trends that promise to enhance how caching is implemented and managed across different platforms and technologies. Here’s how caching could evolve in the future.

Machine Learning-Driven Caching Algorithms

Machine learning-driven caching algorithms are changing the process of optimizing caching technology. These algorithms are getting smarter than ever.

For example, in the near future, we’ll likely witness caching technologies that can analyze patterns in data access and user behavior to predict which data users will need next.

This technology could allow systems to dynamically adjust cache entries for maximum efficiency, improve cache hit rates, and reduce latency.

Edge Computing and Caching

As edge computing grows, so does its synergy with caching.

By processing data closer to its location and where it’s being used, edge caching reduces the need for data to travel long distances.

I’ve pointed out several times that this strategy speeds up response times and decreases the load on central data centers.

For example, one study points out the concept of edge caching, which combines the principles of caching with the technology and architecture of edge computing.

Since edge computing and caching have similar goals, these two will continue to work together harmonically now and in the future.

Integration With Serverless Architectures

Serverless architectures, where developers can build and run applications without managing servers, increasingly integrate with caching technologies.

Caching can significantly enhance serverless applications by reducing the number of times a function needs to retrieve data from a database. This strategy reduces latency and cost per request.

Continued Evolution of In-Memory Caching Solutions

In-memory caching solutions like Redis and Memcached are continuously evolving. These technologies are becoming more sophisticated by adopting features that enhance data consistency, provide richer data structures, and offer better integration with other database and application frameworks.

As in-memory computing becomes more accessible, we’ll likely witness an increase in its adoption across various industries. These trends point to a future where caching not only becomes more intelligent thanks to the adoption of artificial intelligence but is also more critical to the infrastructure of modern applications.

Even as newer technologies emerge, caching will continue to inspire efficiencies and innovations in data processing and delivery, just like it has been since 1965.

So far, we’ve been discussing caching at the textbook level. Now, let’s move to the real world and find out how this technology drives various platforms we interact with daily.

eCommerce Websites

For eCommerce sites, particularly those that run on WordPress, plugins like W3 Total Cache and WP Super Cache help improve site speed.

These plugins cache pages, objects, and databases and are actively involved in CDN integrations.

By caching content, they reduce the load on the server and facilitate quicker response times during high-traffic periods.

For example, if you’re running a promotion on your online store, the last thing you want is a website that takes too long to load because it keeps traveling back to the server’s original storage to fetch user requests rather than load them from the cache.

Social Media Platforms

Social media platforms, such as Instagram, Facebook, and X, use caching to manage the vast amounts of content they serve to millions of users daily.

Imagine a situation where Instagram loads images and videos directly from its original storage location.

That process alone could require tons of resources, and I’m not talking about just memory and storage. For context, Instagram users upload more than 1.3 billion photos daily.

As a result, the app would need a lot of resources to reload these photos directly from storage every time a user sends a server request.

That’s not impossible, but it’s resource-intensive and can lead to high latency issues.

Video Streaming Services

The same concept applies to video streaming services like Netflix and YouTube.

These platforms use caching to store popular videos closer to the user through a distributed network of cache servers.

You probably already know that Netflix has geo-restricted content.

So, let’s say the content in question targets viewers in Africa. In that case, this streaming service will set up geo-specific CDNs and caching technologies for this specific audience.

That way, viewers can stream content without experiencing issues such as lagging.

Gaming Platforms

If you’re a gamer, you already know that the load screen can test your patience.

It’s even worse when you finally load the game and later discover that other features and functions within the game itself are slower than usual.

That’s where caching comes in to save the day.

This technology stores important game assets on local devices or nearby servers for faster retrieval.

Caching is all about achieving these two goals: performance and user experience.

Without excellent performance and great user experience, a particular platform’s design will be ineffective. That’s why caching is still relevant today. It’s like a bearing in a machine. It may seem small and insignificant, but it plays a massive role.

Things could be different tomorrow, but it’s highly unlikely that anything will replace caching. What will likely happen is that caching will become even more sophisticated with artificial intelligence.