So, the question is, did the Big G send us all the wrong way for a decade? Longer answer: if you did march the wrong way for several years, have a word with yourself.
The article quite rightly points out that neither distributed file systems nor distributed computing can be attributed to Google.
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Some of us were already scaling out (admittedly expensive) MPP systems running SQL databases as early as the 1980’s.
Big name retailers, banks and telcos have been running SQL on scale-out database systems for decades.
This approach dates back to Netezza over 15 years ago, and includes the mega-popular AWS Redshift.
The light-bulb moment and conversion to SQL is something Teradata went through over 30 years ago: ‘One day we realized that building our own query language made no sense. And that was one of the best design decisions we have made.
A 100 billion row telco CDR table is over a decade old and runs on a parallel Postgre SQL system. The rational behind attempts to ditch legacy SQL databases is neatly summarised: ‘.’ The likes of De Witt & Stonebraker know a thing or two about this stuff and were early nay-sayers.
To this day I can clearly remember the relief (sorry Grace). One of the first things we do here at VLDB when we have a yearning to set up a database on a cloud platform is to develop an understanding of disk input-output (IO) performance.
It seems a certain section of the IT community is going through a similar realisation: if you want to play with data, SQL was, is, and should be the default starting place. For databases in particular, we are specifically interested in random read performance.
SQL is very deeply embedded in every single organisation I’ve encountered since the late 1980’s. There is simply too much sunk cost and too little benefit in trying to ditch SQL. We’ve had scale-out Teradata MPP systems chomping on SQL since the 1980’s, and newer MPP & SQL players like Netezza & Greenplum for over 15 years.
A low industry profile doesn’t mean something doesn’t exist.