Yeah, there certainly are a few more tricks with regards to scaling RDBMS than the author covered. Depending on what your demands are there are different techniques and protocols which best suite you and can go very far to solving your problem. But with that in mind there may be better ways to solve your problem, and we should not forget about those.

If You start sharding you may get write gains, but you have to work very hard to keep things consistent (depending) and you may have to duplicate shards to make them highly available ($$$). Oh - and later down the track your schema might change in ways which your sharding scheme is just not flexible enough to deal with and depending on who you are that may be too much of a risk.

Besides the issue is really with availability, consistency and performance. It is very hard to scale all three of these together and even your cashcow solutions will hit their limits (although some of their limits are quite high :))

Most of the things he mentions apply to most DB engines, MySQL, MS-SQL, Postgres, Firebird and many editions of Oracle (all of which I've used in data-intensive applications) suffer the same woes. Ultimately it would appear that you went into it reading the article with a narrow minded view of "Yes they do!" instead of "Why don't they?" Also, the disk analogy was for relating information not discussing storage technology or to imply that was what he was using when trying to scale. The portion of vertical scalability clearly presents the option of (and pitfalls therein) using hardware to account for data scalability...