I used to be a huge proponent of ORMs everywhere, but I've come to realize that if you're writing your app in such a way that a developer needs to be able to do any arbitrary data fetch or transformation whenever they want, that's your real problem. The set of retrievals and transformations you want to support should be well-defined, and abstracted into a layer whose interface allows the level above it to only think in terms of models and not their backing store.
After you have that, then it doesn't even matter on the backend. The models you present to the layer above can have complex and changing relationships to the actual storage -- maybe they contain data which is derived from what's in the database, but transformed after being fetched so that none of their properties actually correspond to a column or a field in a store. In my experience -- having seen the tragedy that is a Rails project gone full ActiveRecord -- this pattern enforces an excellent separation of concerns and constrains a problem which can otherwise grow unboundedly in complexity.
I don't really agree; I think you either need to have a very thin layer between your DB facts and your domain, or else use the DB as a kind of persistence layer for a complex graph.
The latter only really works if you've got a primary implementation language and aren't integrating lots of applications / libraries written in different languages communicating with the same database. You need to go down the SOA / distributed RPC / FFI route to integrate different languages, and that has its own complexities.
Personally I prefer treating the DB as a canonical store of facts. Models with a lot of code are pretty suspect. Retrievals can be tuned to just the facts required, ma'am - you don't accidentally drag in the banana + gorilla + whole forest. Doesn't stop you building a higher-level service layer if that's what you need, either. You'll need that when you scale up anyway; chatty models won't work at that level either.
Yeah, I'm saying that as your app grows out of being a simple CRUD app into something more useful and involved, there will be less of a relationship between what you need to store things efficiently, and what you need to present them well. Your model will become more graph-like, probably. For this reason, patterns designed around AR-style models will fail to scale. I disagree that this only works in a mono-lingual environment, although you will need tooling and infrastructure to support it; a model-centric architecture typically doesn't afford the possibility of multi-lingual support.
The code doesn't go in the models, it goes in the service/arbitration layer. DB as a store of facts is obvious -- DB as a 1:1 representation of what yet-unforseen features, UIs and platforms will need is a naive and limiting assumption. You have to build your application in a way that future product needs won't be constrained by storage and modeling decisions, which is a tension that Rails apps frequently encounter.
After you have that, then it doesn't even matter on the backend. The models you present to the layer above can have complex and changing relationships to the actual storage -- maybe they contain data which is derived from what's in the database, but transformed after being fetched so that none of their properties actually correspond to a column or a field in a store. In my experience -- having seen the tragedy that is a Rails project gone full ActiveRecord -- this pattern enforces an excellent separation of concerns and constrains a problem which can otherwise grow unboundedly in complexity.