SAS is developed in a corporate setting, and you might be waiting a long time before you can try that cool trick you read about online.
In SAS you don't have to worry. The reputation of the corporation depends on its ability to deliver a quality product.
When I write SQL in SAS I am confident that my co-workers will understand my program. With R, everyone writes SQL differently. That's a barrier to collaboration.
If something in R is malfunctioning, it is not clear who is accountable.
With SAS, I know exactly where to direct my anger.
It has something that SAS hasn't got: an engine.
It's much more difficult to apply some of these methods in R. I'm limited to the 8G of RAM on my computer, and I'm constantly bumping my head on the ceiling.
But R has served me better for data exploration and visualization. Plus it's free. Can't argue with that 🤑
(PS - my tweets should never be taken as opinions of StatCan)