Today, this paper seems to address something that is a nonissue - throughout the duration of my career in computer science I've been of the mindset that "one size fits all" has no place. It's strange to me to think how ubiquitous the DBMS was in times past - amazing that we were at a point when all of the systems I think of today as distinct - OLAP, OLTP, analytics, warehousing, etc. - were run through the same platform. I don't know if this paper in particular was influential in causing the shift to today's mindset, but in any case, the shift certainly occurred.
One interesting question that I think arises from this is - will there ever be a time when we have systems that are so efficient we can again return to a one size fits all paradigm? It currently doesn't seem likely, but that would seem to be the "holy grail" of sorts. The Hadoop ecosystem today does provide at least a unified platform that many such systems can interact upon, with a unified data later (e.g. HDFS, Tachyon) and unified schedulers (Mesos, YARN).
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