Heh... of course Steve is being "relative" here and so was the article he cited.  I absolutely get that what people think is large (for example, some of the larger health insurance  companies) really isn't compared to some of the juggernauts of the computational world (NASDAQ, for example, which suffers "Billions of transactions per day and has "Multiple Petabyte Databases" and single tables with "Quintillions of records" https://www.youtube.com/watch?v=AW87RzZJ0Z0).  Certainly, most of the stuff that most of us (denizens of SQLServerCentral.com) deal with is, indeed, quite "small to medium scale" compared to NASDAQ or even companies contained in the following list of companies ( https://customers.microsoft.com/en-us/search?sq=&ff=&p=0&so=story_publish_date%20desc )

I also understand what is being said in the following quote from the article...

There's an article that I think illustrates this well, and might be worth passing along to your developers. It's called Why Amazon DynamoDB isn't for everyone and it's worth a few minutes of your time to read. The gist of the article is that a NoSQL system, like DynamoDB, isn't as simple and easy as you expect. It also says that for many applications, a relational database is a better choice because it's often better understood and will solve most problems at small scale. For most of us, we don't really get past what I'd consider small to medium scale, and so we should stick with relational systems. 

The cited article starts off by saying that...

And, yes... despite the fact that there were "only" ""hundreds of millions of products" from Thanksgiving through Cyber Monday", there were also a huge number of transactions for each product sold that control the warehouse robots and "smart" conveyer systems ( http://money.cnn.com/2017/11/29/technology/amazon-cyber-monday/index.html ) very likely (IMHO) bringing the number of related data transactions to the "billions" per day that the NASDAQ sees.

That cited article and Steve's good article on the same subject seem to be suggesting that when you actually do approach or achieve truly "large" scale, that an RDBMS isn't the way to go and, yet, there are huge RDBMS's, such as what is powering NASDAQ, that have been using an RDBMS for a long time. 

That's my only point of contention with the article. Size doesn't actually matter.

That being said and what DOES matter, I very much DO agree with the main thrust of the article.  We have computational juggernauts like NASDAQ and Amazon that have similar scale (again, IMHO).  The former uses an RDBMS and the latter uses something that (apparently) doesn't.  Why is that?  The answer is indeed "The Engineers" but, again, to highlight my point of contention with the article, it has nothing to do with scale as to whether or not an RDBMS was used.  It was the know how of "The Engineers" that allowed one giant of the industry to use an RDBMS and the other to use something else.

Heh... and to rub it in a bit for the people (and especially the self proclaimed "engineers") that I've had to interview in the past, I'm thinking that the Engineers that built both the NASDAQ and Amazon each knew how to get the bloody current date and time from the system being used . 😉