CAP theorem

Here's the CAP theorem in a nutshell:

In distributed systems, you can fully guarantee only two of these three things:

• Consistency (C): Everyone sees the same data at the same time.
• Availability (A): The system always responds to requests.
• Partition Tolerance (P): The system keeps working even if parts become disconnected.

You have to choose two:

• CA: Great for consistent data (like banking).
• CP: Ideal for reliable systems (like safety controls).
• AP: Perfect for high uptime (like social media).

The CAP theorem helps you make smart trade-offs when designing distributed systems.

Inspired from : Lesson 149 - Caching and CAP Theorem by Mark Richards

References for the CAP Theorem:

• Brewer's original paper: "Towards a Theory of Fault-Tolerant Distributed Systems" by Eric Brewer (2000): https://medium.com/@gurpreet.singh_89/understanding-the-cap-theorem-consistency-availability-and-partition-tolerance-e7faa5103638

• An Illustrated Proof of the CAP Theorem: A graphical explanation with clear visuals: https://captum.ai/tutorials/Multimodal_VQA_Captum_Insights

• What is the CAP Theorem?: A comprehensive explanation by IBM with diagrams and examples: https://www.ibm.com/topics/cap-theorem

• CAP Theorem for Databases: A focused explanation on how it applies to database systems: https://www.bmc.com/blogs/cap-theorem/