10/29/2013

The IT Spats Continue

Since I got into IT, there has been raging debates over just about everything.

First there was VB6 vs .  Object Oriented purists wanted more than Visual Basic 4,5,6 could offer.  Microsoft ventured forward with Dot net without much concern for the VB developers.  Move foward or get left behind.  However, VB6 and ASP still exist in many IT Shops today.

Then c# vs Java.  Microsoft got in trouble with their J# so they conjured up a new (almost identical) language called c sharp.  It competes head on with Java.  What I like is MS offers a single IDE with multiple languages (VB.net, F#, C#, they even have Cobol for .net).  Java has many IDE and many flavors of Java.  I find it's easier to stay current with MS.  Also Java is no longer open source, it's been acquired and is somewhat propritary.

Then we have the battle between SQL Server vs Oracle.  Two giants going head to head, buying up every company they can find to integrate into a mammoth arsenol of offerings.  I worked with Oracle first 10 years of my career, front end seemed non existant except command line editing in SQL Plus, or purchase an expensive 3rd party vendor tool.  MS has grown from a fun app to an enterprise app since 2000.  Personally, I like SQL Server.

Traditional SSAS vs Tabular Model was more recent.  The cube purist who made some good bank $ for the past 10 years were upset that their bread and butter was being challenged by a more user friendly verison called Tabular.  You could get up to speed in hours, not months.  It ran in memory and was super fast.  Bottom line, SSAS cubes aren't going away anytime soon.  Learn both.

And now we are at Relational DB vs Hadoop. Vendor proprietary datbases verse Open Source unlimited storage, distributed architecture across commodity servers.  Hadoop picks up where Relational stops.  Huge volumes, complex data, unstructured.  For  now they both serve a purpose.  If you want transactional data with instant writes, choose OLTP.  If you want cubes choose OLAP.  And if you want to crunch huge volumes of data, use Hadoop.

And so, like sands through an hourglass, so are the days of our IT lives.

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