Mainframe to Distributed SQL, Part 3: Distributed Database Architecture

Distributed database architecture is becoming increasingly popular due to its ability to address the growing demands for scalability, availability, and performance in modern applications. Unlike traditional centralized database architectures, distributed databases store and process data across multiple nodes or locations, offering numerous advantages such as improved fault tolerance, seamless scalability, and enhanced data locality. Distributed SQL databases have emerged to combine the advantages of NoSQL (cloud-native scalability and resilience) with the strict schema and ACID guarantees of traditional relational databases. These databases do not require manual sharding and offer ACID guarantees, making them ideal for transactional workloads and applications requiring high data consistency. The principles of distributed databases include distribution of data, transparency, scalability, reliability and availability, and decentralized management. Distributed systems use load-balancing techniques to distribute workloads evenly across multiple nodes, enabling parallel processing and improved access times. They also support horizontal scalability by allowing the addition of additional instances or nodes to handle increased loads. Distributed databases inherently offer advanced fault tolerance and resilience mechanisms, making them ideal for maintaining high availability and robust disaster recovery. Data replication and consensus protocols like Raft ensure consistency across distributed nodes and prevent conflicting decisions by different leaders. The operational complexity of managing a distributed database can be more challenging than a single-instance DB, but managed DBaaS options can alleviate this issue. Despite the potential downsides, distributed databases offer significant benefits in terms of scalability, availability, and performance, making them an essential tool for modern data management.