I think he is being relative here. I could be wrong there, but that's how I read it in the sense, small in this context may be large for you.

There are plenty of case studies that show both SQL Server and Oracle can solve very large problems. However, as the article highlights, when you don't really have a data model or don't attempt to define a proper one with or without the proper expertise to tune the tech you have, then you're left with a pretty large problem that does not just mean an increase in data size. It could just mean poor business process. Therefore, taking a piece of tech with the assumption that it has great ease of use that your business can easily pivot to that you can just throw large quantities of data at, seems like a good choice until you realize it's not that simple.

Kind of reaffirms the notion that it may not actually be a tech issues as much as a business process issue. I.e.: maybe your RDBMS could handle that large problem afterall, you're just doing it wrong or don't want to do it right. Which is sadly very true in a large amount of cases I bet.

Regardless, it all translates to using the right tools for the job with the added excerpt -- the right tools your team knows how to use. Not what some hot new marketing blog is telling you to use.