You're not necessarily keeping track of all the old values over time. Rather, the core idea is that you program in terms of abstractions that are explicit about

You're not necessarily keeping track of all the old values over time. Rather, the core idea is that you program in terms of abstractions that are explicit about time. That is, you write your program in terms of streams of events or signals. You have signals and events, but you never ask about the value right now; instead, you take these two abstractions and combine them in different ways to get a reactive network. In a way, it's similar to dataflow programming or circuit design: you connect up "wires" into a network that can constantly push through data. Depending on how you write this network, you will need to remember different amounts of past data at runtime. If you write your event/signal network carefully, you do not need to keep a history of too many prior values at runtime. This is one of the things modern FRP libraries really try to help you with: writing networks that are efficient. At least the ones I've tried are good at this--I haven't had many space problems in my programs so far. In summary, this is a potential issue, and you may have to be a little careful in how you write your FRP code. However, modern frameworks try to make it easy to avoid these pitfalls, and there is no fundamental reason you can't use memory efficiently with this model.