The reason most of the time RDBMS are a fit most of the time is because majority of data is inherently relational. It seems that the problem for people with using relational databases is that there's a learning curve to use it. This makes NoSQL much more appealing at first, but once you start using document store and unless your data is trivial (everything can be referenced with a single key) you will realize how hard it is. Sure, NoSQL is easy because you don't have schemas, relations, transactions etc, but because it doesn't have all of that now you have to implement this in your application which is not an easy task.

Another thing (which often overlooked) is that because relational database typically matches data model better your data will take less of space than when stored in NoSQL. With Postgres there's also the extensibility.

I learned this myself, we had a database that stored mapping of IP to a zip code and latitude/longitude to a zip code. The database was on MongoDB, but it wasn't too big (~30GB) the thing is that to maintain a performance all of the data needed to fit in RAM.

I was a bit curious and decided to see how Postgres would deal with this. So I loaded ip4r extension (to store IP ranges) and PostGIS to enable lookups on latitude/longitude. All the data fit in ~600MB, and with proper indexes postgres returned all queries instantly (sub milisecond).

The Mongo was running on 3 c3.4xlarge instances, but postgres would be fine on smallest available one and would still be able to cache whole database in RAM.