Mastering System Design [02]: Data Management, Scaling, and Distributed Systems

As systems grow, managing data efficiently and ensuring scalability become increasingly important. This article will cover essential topics in data management, scaling strategies, and the fundamentals of distributed systems, providing a comprehensive understanding of how to design systems that are robust, scalable, and efficient.

1. Distributed Systems

Introduction to Distributed Systems: Distributed systems consist of multiple independent components (nodes) that work together to perform a collective function. These systems are designed to handle large-scale data processing and provide high availability, fault tolerance, and scalability.

Challenges of Distributed Systems:

• Consistency: Ensuring all nodes have the same data at the same time.
• Availability: Making sure the system is operational even if some nodes fail.
• Partition Tolerance: The system continues to function even when network partitions occur.

Real-World Example: Google Spanner

• Google Spanner is a globally distributed database designed to offer strong consistency and high availability. It uses synchronized clocks to provide external consistency, meaning transactions are consistently ordered globally.

Purpose Solved: Distributed systems allow applications to scale horizontally, handle large data…