More importantly, I think, there are issues with some data structures that are not well supported by postgres or any other DBMS (relational or otherwise). I do a lot of text analytics work and there are things I need to store about spans of text that I could model in a relational fashion but I don't because it would lead to 99% of my data being foreign keys and row metadata.
There will always be domains where you need highly specialized combinations of data structures and algorithms that are not efficient to model relationally and even less in terms of some of the other datamodels that you find in the NoSQL space.
That said, I found that even in natural language processing, RDBMS do a lot of things surprisingly more efficiently than conventional wisdom would have it. Storing lots of small files for instance, something that file systems are suprisingly bad at.
Sometimes I'm surprised how many people like to complain about premature optimization using languages that are hundereds of times slower than others but then go ahead and use horribly inflexible crap like the BigTable data model just in case they need to scale like Google.
Of course that's off topic because it's not remotely what Hickey proposes.