Earlier quoted context omitted.
In a typical architecture, the DB stores data, and the backend calls the DB to make updates and compile views. Here, the "views" are defined formally (the P-states), and incrementally, automatically updated when the underlying data changes. Example problem: Get a list of accounts that follow account 1306 "Classic architecture": - Naive approach. Search through all accounts follow lists for "1306". Super slow, scales…
So... at a high level, early React for data? In other words, letting a framework manage update dependency graph tracking, and then cascading updates through its graph in an optimized manner to enhance performance? Obviously, with tons of implementation difficulties and details, and not actual graph structures, but as a top level analogy.
To be honest any parallel with frontend here is meaningless, reactivity and all the concepts at play have existed long before JS and browsers came along, it’s easier to explain from first principles.