Consistency vs Availability | CAP Theorem in System Design 🔥

*CAP Theorem in Practice — Consistency vs Availability* What actually happens when your distributed system has a **network failure**? In this video, we break down the *CAP Theorem* using a simple application and gradually introduce multiple servers, database replication, and finally a network partition. You'll understand: 🚀 *What is CAP Theorem?* • Consistency (C) • Availability (A) • Partition Tolerance (P) 🚀 *CAP Theorem in Practice* • Single-server application • Multiple servers behind a Load Balancer • Database replication • What happens during a network failure • Why the CAP trade-off matters during a partition 🚀 *CP vs AP* • When should you prioritize Consistency? • When should you prioritize Availability? • Payment vs Inventory systems • Product pages, Reviews & Recommendations • Search systems 🚀 *Types of Consistency* • Strong Consistency • Eventual Consistency • Causal Consistency • Read-Your-Writes Consistency 🚀 *System Design Interview Perspective* CAP Theorem is not just a theoretical concept. It is useful during *requirement gathering and trade-off discussions* in HLD/System Design interviews. We'll also discuss how different distributed services can make different consistency and availability trade-offs. If you're preparing for **System Design / HLD interviews**, this video will help you understand CAP through practical examples instead of just memorizing the theory. 📌 *Topics Covered:* CAP Theorem, Distributed Systems, Consistency, Availability, Partition Tolerance, CP vs AP, Database Replication, Network Partition, Strong Consistency, Eventual Consistency, Causal Consistency, Read-Your-Writes Consistency, System Design, HLD Interviews 👉 Subscribe to *Chalk To Code* for practical Software Engineering, System Design, HLD, Java, Databases & Distributed Systems content. 00:00 - Introduction to CAP Theorem 00:18 - Problem Statement: Bank Account System Example 01:50 - Scaling the System (Horizontal vs Vertical Scaling) 03:00 - Database Bottleneck & Adding Replicas 04:22 - Network Failure Scenario & Data Inconsistency 06:10 - What is CAP Theorem? (Consistency, Availability, Partition Tolerance) 07:04 - Consistency (C) Explained 08:26 - Availability (A) Explained 08:52 - Why You Must Choose CP vs AP in Real-World Systems 10:05 - Interview Trap: Is Amazon CP or AP? (Microservices Trade-offs) 10:46 - Real-World Example: Payment Service (CP) vs Search Service (AP) 12:56 - Types of Consistency Explained 13:00 - Strong Consistency 13:16 - Eventual Consistency 13:48 - Causal Consistency 14:38 - Read-Your-Writes Consistency 15:05 - Conclusion & Next Steps