CAP Theorem Explained Like Choosing a Pizza Delivery

Let’s say you’re craving pizza and decide to order from your favorite pizza place. You have three things on your mind: you want the pizza to arrive hot and fresh (Consistency), you want it to arrive on time (Availability), and you want to be sure the delivery guy finds your house (Partition Tolerance). Now, according to the CAP theorem in distributed systems, just like with pizza delivery, you can’t have everything perfect all at once — you have to make trade-offs. Let’s break it down.

C is for Consistency: Hot and Fresh Pizza

Consistency in the CAP theorem is like making sure that every time you bite into that pizza, it tastes exactly how it should. If you ordered extra cheese, you expect that every slice has that ooey-gooey goodness.

In a distributed system, consistency means that every read receives the most recent write. In other words, whenever you access the data, it should be the latest and most accurate version, just like getting a hot, fresh pizza every time.

For example, a user checks his account balance and knows that he has 500 rupees. He spends 200 rupees on some product. Hence the amount of 200 must be deducted changing his account balance to 300 rupees. This change must be committed and communicated with all other databases which holds…