Around 10 years ago I joined Amazon Web Services and that’s where I first saw the importance of trade-offs in distributed systems. In university I had already learned about the trade-offs between consistency and availability (the CAP theorem), but in practice the spectrum goes a lot deeper than that. Any design decision may involve trade-offs between latency, concurrency, scalability, durability, maintainability, functionality, operational simplicity, and other aspects of the system—and those trade-offs have meaningful impact on the features and user experience of the application, and even on the effectiveness of the business itself.
Perhaps the most challenging problem in distributed systems, in which the need for trade-offs is most apparent, is building a distributed database. When applications began to require databases that could scale across many servers, database developers began to make extreme trade-offs. In order to achieve scalability over many nodes, distributed key-value stores (NoSQL) put aside the rich feature set offered by the traditional relational database management systems (RDBMS), including SQL, joins, foreign keys, and ACID guarantees. Since everyone wants scalability, it would only be a matter of time before the RDBMS would disappear, right? Actually, relational databases have continued to dominate the database landscape. And here’s why: Keep reading