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Good article, but it and a lot of the comments here seem to be conflating SQL as a language and Postgres (or other RDBMS implementations.)

For the record, I like both these things and they often go together well. But once your data gets too big for Postgres, you don't have to immediately jump to NoSQL: modern distributed SQL tools like Presto are quite good and can let you continue to use the same SQL interaction patterns, even at the terabyte or petabyte scale.

You have to be a little more aware of what's going on under the hood, so you don't write something pathological, but it's quite a powerful approach.

I am even using Presto for a lot of what would normally be considered ETL: using SQL to select from a "dirty" table and inserting into a "clean" table on a schedule.

And presto's rich functionality for complex data types (maps and arrays) as well as window functions makes some pretty challenging things possible.

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