Caching is one of the Unsung Heroes of Application Performance

After reviewing several application codes and architectures, it's evident that many low to mid-level companies either neglect caching or implement it inefficiently. Usually, a significant amount of time is often spent optimizing databases and their queries and ultimately caching tends to be overlooked.

Why Databases Slowly Become the Bottleneck

Usually for applications, things slow down when lots of people use them. One reason is the database, like a big storage room for data. As more people come, the database gets overwhelmed with requests. Why? Because it's like everyone wants to get into the storage room at once, causing a traffic jam.

Several factors contribute to this slowdown on the Database side:

1. Increased Load: As the user base expands or the application gains popularity, the database must handle a higher volume of requests, leading to increased query times and potential contention for resources.

2. Complex Queries: Complex data retrieval queries, joins, and aggregations can strain the database server, especially if proper indexing and optimization techniques are not employed.

3. Scaling Challenges: Scaling databases horizontally (adding more servers) is challenging and expensive, particularly for traditional relational databases. Vertical scaling (upgrading server hardware) has its limits and can be costly.

4. Data Volume Growth: Over time, the volume of data stored in the database can grow exponentially, further exacerbating performance issues, especially if data retrieval operations are not efficiently optimized.

Why Most People Don't Use Cache

Even after people get to know that the Database has become the bottleneck for their application still many people don't take the Caching route. I observed these patterns in my experience for not taking the Caching route:

1. Complexity: Implementing caching mechanisms requires additional development effort and introduces complexity into the application architecture.

2. Data Consistency Concerns: Caching introduces the risk of stale or outdated data being served to users if not managed properly. Maintaining data consistency can be challenging, especially in applications with frequent data updates.

3. Lack of Awareness: Many don't understand the benefits of caching or how to effectively integrate it into their applications.

Why We Should Use Cache

1. Speed Boost: Cache saves time by keeping frequently used stuff close by, so you don't have to wait for the storage room.

2. Less Stress on the Server: When the cache helps, the storage room doesn't get as crowded, so it can handle more people without slowing down.

3. Saves Money: With cache, you might not need to buy bigger storage rooms (servers) as soon, saving you cash.

4. Happier Users: Faster applications mean happier visitors, who are more likely to stick around.

Ways Cache Can Be Implemented

There are several approaches to implementing caching in applications, each with its own benefits and trade-offs. These are some of the common ones:

1. In-Memory Caching: Store frequently accessed data in memory for rapid retrieval. Popular in-memory caching solutions include Redis and Memcached. It's like putting stuff you use a lot on a nearby shelf (in-memory caching), like putting your favourite snacks in an easy-to-reach spot.

2. Client-Side Caching: Cache data on the client side using techniques such as browser caching or local storage. This can reduce server load and improve perceived performance for users.

3. CDN Caching: Content Delivery Networks (CDNs) cache static assets such as images, CSS, and JavaScript files, reducing latency and improving load times for users across the globe.

4. Database Query Caching: Cache the results of frequently executed database queries to avoid redundant database operations and speed up data retrieval.

Cache Eviction Methods

One thing many miss is Cache eviction. This is very important or else whatever nightmares you thought about cache those come to life. Here are some common cache eviction strategies:

1. Time-Based Eviction: Set a time-to-live (TTL) for cached items, after which they are evicted from the cache and considered stale. If you leave your favourite snacks in the easy-to-reach spot for a long time they get spoiled right. After some time we need to throw them out.

2. LRU (Least Recently Used): Evict the least recently accessed items from the cache when it reaches its capacity limit.

3. LFU (Least Frequently Used): Evict the least frequently accessed items from the cache to make room for new data.

caching is sometimes overlooked or underutilized. cache can be a big help for websites, making them faster, cheaper and more enjoyable for everyone.