I still didn't have a single use-case to use JSON columns yet. Sometimes I feel that JSON columns are made for people who don't want to properly design their domain model. Big mistake.
Interesting point, but I wonder if there's a little confirmation bias and/or circular logic there.
In other words that you don't see a use case for JSON columns because you don't think it's good DB design.
I know I have used them after decades of RDBMS work, and it feels like I'm "cheating" a bit. But they really do make sense for some use cases that can be harder to achieve with traditionally normalized RDBMS alone. For instance, for configuration options or scenarios where different objects may have a few different attributes, but are largely the same.
If you've ever used an entity-attribute-value data model or otherwise ended up with table proliferation or a bunch of nullable columns to accommodate the latter use case, you might appreciate the simplification JSON columns offer.
I think it is the same misguided discussion as strongly, staticall typed vs weakly typed languages.
(Mind I mean the discussion is misguided, not you)
The problem is that relational model is a one solution to certain problem of when you want to pay the price of enforcing the model of your data. Relational database is when you pay all the cost upfront.
With MongoDB I have other options.
It does not mean they are necessarily better options. But some of them are better in some situations, for example when rapid prototyping. Or when you need to preserve data in different formats as the application evolves.
Personally, if you can, you probably should model your data upfront. But it is good to have other options, sometimes.
The main use case I find myself reaching for JSON/JSONB fields is unstructured map-like metadata, like KV tags on a resource, where the data model/domain has no expectation that any given field is set.
