For example, that pure functional programming is easier to reason about. True, but as soon as you have to simulate state it's more complex that just having state.
I actually disagree here. It's true that the traditional state model of "everything gets everything" makes writing code very easy. Everything can see and modify everything else, so you never have to worry about manually passing state around.
This makes the code easy to write, but very difficult to debug. A function can do something different every time you call it with the same arguments. That is hard to reason about.
There are actually a few layers involved, the programming language, the data types, and the app code. In a non-functional language, you really ignore the data types and let your app code interact with the language. ("var foo = 42; ...; foo++")
In a language like Haskell, it's important to think about your data types. Your state abstraction will live there, and then your app code will not have to worry about the details of passing state around. So in the end, your app code looks the same in either paradigm.
An advantage about this approach is an increase in generality. If you just have some variables hanging around and some "stuff" that uses them, that's all you can ever have. If you interact with state via well-defined interfaces like the Monad or Applicative Functor, you can build abstractions that work on all types like this. This has worked very well for Haskell. (An example is the do syntax for monadic computation. Although you have functional purity, your program looks imperative. This, IMO, is the best of both worlds. There is some complexity under the hood, but you get code that's easy to read, write, and reason about.)
I agree with you here 100%. Maybe this is a good pathway to explaining why relational databases are good ideas in much the same way as having a programming strategy that uses a backbone of pure functions. This purity-dividend is exactly why the relational model is such a good strategy for database management.
In the same way haskell lets you separate your pure functional code from your monadic code, giving you the ability to referentially transparent reasoning and construct imperative machines where you must, the RDBMS approach applies total logic programming to database management. It's frustrating because your code cannot all live in one language as it can in Haskell, but the separation of pure from impure is exactly where the value is coming from.
RDBMSs focus on values and total computations (you know they will halt, making it even easier to reason about queries than non-total functions) allows you to isolate simple logic programs from the rest of your impure non-total code.
Navigational databases don't give the same benefits because they are not value based nor are they total. They are the imperative-model of the database world, and though they are easy to write, they will end up difficult to debug, maintain, and keep coherent.
I agreed with your overall point, but I was expanding on part of what you were saying:
You seem to appreciate how Haskell allows you to separate your pure code from your non-referentially transparent monadic code. This gives you reasoning where you can have it, and you use monads where you can't.
I'm just saying that same argument applies in databases where using a relational database allows you to separate your total code from your pure code. You use the value-based relational strategy where you can have it (necessary and sufficient for database management), and you use functional (or imperative) programming where you can't.
I actually disagree here. It's true that the traditional state model of "everything gets everything" makes writing code very easy. Everything can see and modify everything else, so you never have to worry about manually passing state around.
This makes the code easy to write, but very difficult to debug. A function can do something different every time you call it with the same arguments. That is hard to reason about.
There are actually a few layers involved, the programming language, the data types, and the app code. In a non-functional language, you really ignore the data types and let your app code interact with the language. ("var foo = 42; ...; foo++")
In a language like Haskell, it's important to think about your data types. Your state abstraction will live there, and then your app code will not have to worry about the details of passing state around. So in the end, your app code looks the same in either paradigm.
An advantage about this approach is an increase in generality. If you just have some variables hanging around and some "stuff" that uses them, that's all you can ever have. If you interact with state via well-defined interfaces like the Monad or Applicative Functor, you can build abstractions that work on all types like this. This has worked very well for Haskell. (An example is the do syntax for monadic computation. Although you have functional purity, your program looks imperative. This, IMO, is the best of both worlds. There is some complexity under the hood, but you get code that's easy to read, write, and reason about.)