AWS Aurora, ElastiCache Patterns & DynamoDB — The Complete Data Layer

<p>Hey dev.to community! 👋</p> <p>I've been working on a side project for a while now and finally got it to a point where I feel comfortable sharing it publicly. It's called

<p>Every backend engineer has heard the advice: add a cache. It will make your system faster. And they are right, it will. But a cache that is not properly understood is one of

<blockquote> <p>Skip the theory rabbit holes. This is the caching knowledge that shows up in system design interviews, code reviews, and the 2 AM production incidents nobody

<p>Every high-traffic system eventually hits the same wall: your data store can't keep up. For us, the breaking point came when a simple product lookup — backed by Elasticsearch —

<ul> <li> <strong>Book:</strong> <a href="https://www.amazon.com/dp/B0GYMFPTWV" rel="noopener noreferrer">System Design Pocket Guide: Fundamentals</a> </li> <li> <strong>Also by

<p>Caching is one of those things that sounds optional until your database starts getting hammered at scale, your response times creep up, and you realise you've been querying the

<p>In the early days of a startup, functional is the goal. You write a query, you get the data, and you send it to the frontend. But as we scaled past 50,000 users, that

<p>Redis is a data structure server that lives in memory. It's fast because reads and writes never touch a disk during normal operation. It's versatile because it supports more