Making either of those your line in the sand for what a developer should and shouldn’t know is arbitrary. I don’t know a ‘Scala’ full-stack developer that could do advanced optimisation on React render times, or a ‘React’ developer that knows transaction isolation.
Not knowing either of these does not make you an unworthy developer and unless you have a specific need for these skills it probably does more harm than good expecting everyone to know them.
It's very expensive to acquire customers. It gets even more expensive when you have dirty data from incomplete domain modeling.
At the most basic conceptual level, the business of software rests on reading inputs correctly, processing them, and writing the right outputs with strong guarantees. SQL is historically the most sophisticated, powerful, common and cross platform way to do that in a structured manner that is easy to reason about for a vast majority of use cases. You can layer an application on top of the foundation of an appropriate data model, but the appropriate data model is a root requirement to even get to a passable prototype. That is why gradual mastery of it yields such outsize payoffs compared to mastering other skills.
What about security? Your business won't succeed if you're hacked daily.
What about monitoring? If you're losing data and don't even know it, you're creating compound technical and potential business debt.
What about performance? Once you have a perfect data model, no amount of trying to optimize it will improve your business further. Optimizing other parts of the application can.
Basically everything is important, saying that just because someone isn't an expert in one phase that they're not as good of a developer is myopic.
The truth is, you need to be good enough at all of the high priority parts of technical competency. Security, monitoring, performance -- sure, all of those are also extremely important. They're all places where unforced errors can be introduced that can and do hurt the business -- sometimes catastrophically or fatally.
With that said, to not recognize the evergreen utility of domain design skills is ignorant. You will never get the luxury to worry about security, monitoring, or performance if you don't build the state machine that makes the right outputs out of the right inputs because you will either never sell it to a customer, or lose that customer when they choose a competing solution which actually does what it's supposed to do.
It's not true that everything is equally important. I think that's a myopic way to look at software development without considering the business impact of key crucial areas where software design and maintenance intersect with stakeholders.
Which can be the consequence of setting the wrong isolation level: http://www.bailis.org/papers/acidrain-sigmod2017.pdf
The distinction is similar to a property developer and a civil engineer. Both create buildings, but one does it at scale by offloading functions to known entities and prepackaged solutions, while the other understands one domain in depth.
Both are needed in any team or organization, because not every solution needs to be "engineered" (a Dockerized Redis instance without SSL or auth behind a corporate firewall may survive untouched for a decade), but sometimes you have to engineer something that withstands gale-force winds at 1000 ft height.
I mean, this is still arbitrary. There are millions of small businesses worldwide that do fine with terrible records, but making on-going sales.
If you don't make any sales because of constant outages, you could argue that's worse than trying to deal with corrupted data, especially if you have log files or some other method to recover corrupted data anyways.
My point is that the very root of what gives software value is something deeply industrial -- it is a machine that can do something over and over correctly, reliably and without regressions. If you take away that reliability to be depended upon by a business, you are no longer building an industrial strength solution -- you're building a toy.
As long as you have both covered to a reasonable degree within your company/team it’s a waste of time arguing who’s got the most important info in their brains.
SQL is intrinsically very close to the metal of your business logic, especially when it comes to general business logic. General business logic is typically most critical and risky around the surface of payments. A JavaScript bug on your site around your shop preventing checkouts is very bad because you are indeed losing cash by the minutes. A poor domain model that doesn't properly associate active promotions to cart order lines could result in an incorrect charge amount and an irate customer.