Caching is a technique used by software engineers to improve performance by storing frequently accessed data in memory for quick retrieval later. It's like having a secret stash of your favorite snacks hidden away in your desk drawer at work, except instead of snacks, it's data, and instead of your desk drawer, it's super fast memory on a server somewhere.

How to use it in a sentence

• "We should add some caching to this API endpoint, so we don't have to keep hitting the database every time some TikTok influencer's bot farm decides to DDOS us with requests for their profile data."

• "Looks like we forgot to update the cache when we changed that user's profile picture. Now they're stuck with that awkward phase from 2015 where they thought frosted tips were making a comeback."

If you actually want to learn more...

• Rethinking Caching in Web Apps: This article explores some of the challenges with typical caching architectures in web apps and proposes some alternative approaches, like separating business logic from network communication and using precomputed caches.

• Turning the Database Inside-Out with Apache Samza: This post dives into some of the problems with application-level caching, like cache invalidation and race conditions, and looks at how databases handle similar issues with index building.

• Caching Strategies and How to Choose the Right One: An overview of different caching strategies like cache-aside, read-through, write-through, and write-back caching, with pros and cons of each approach.

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