The traditional CRUD (Create, Read, Update, Delete) pattern has been a mainstay in system architectures for many years. In CRUD, reading and writing operations are usually handled by the same data model and often by the same database schema. While this approach is straightforward and intuitive, it becomes less effective as systems scale and as requirements become more complex.
For instance, consider a large-scale e-commerce application with millions of users. This system may face conflicting demands: it needs to quickly read product details, reviews, and user profiles, but it also has to handle thousands of transactions, inventory updates, and order placements efficiently. As both reading and writing operations grow, using a single model for both can lead to bottlenecks, impacting performance and user experience...
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