IBM vs Open Source

I have spent more than 14 years in open source world. Organisations choose to go with proprietary stack from Microsoft, IBM, Oracle or the open source / LAMP stack. Anyone loving the craft of creative output loves toying with the latter, as you have so much more control. 

In 2013 on the one hand you have Meteor, Nodejs, Vert.x, jQuery, DOJO and on the other hand drag and drop frameworks with less need for coding. If we are to become a mature and scale to stars, we need to write less brittle code. For simple business applications the challenge of choice is real. More money spent on licensing proprietary products or more money spent on staff.

CIOs tend to get influenced by Gartner Magic Quadrants and choices have long lasting impact. I am playing with the IBM system including heavy weight products such as MQ Series, Websphere Message Broker, IBM Datapower Appliance, and soon BPM, ODM and WAS. The products themselves are tightly integrated and it will be hard for any organisation to move away from IBM products once locked in. NZ Police Department is going to spend over 1.2 billion NZD to get rid of IBM products which may have costed them 100 million $ to get in. Surely this cost was no accounted in project plans :-)

I am not a purist, nor is it my highest calling to take up the battle of open source vs proprietary and prove lower TCO either way, I intend to make the best of what is given with best design patterns for a large organization and fill in my coffers in the process ! Long live the complexity in design and divorce of senior management with fundamental engineering principles !

Where data is Big

Big Data is all the rage which our CIO likens to Data Warehouse I am told:

A closer look at some interesting tools. Skytree looks like a shiny tool from sci-fi, "Skytree is more focused on the guts than the shiny GUI. Skytree Server is optimized to run a number of classic machine-learning algorithms on your data using an implementation the company claims can be 10,000 times faster than other packages. It can search through your data looking for clusters of mathematically similar items, then invert this to identify outliers that may be problems, opportunities, or both. The algorithms can be more precise than humans, and they can search through vast quantities of data looking for the entries that are a bit out of the ordinary. This may be fraud -- or a particularly good customer who will spend and spend."

http://www.infoworld.com/d/business-intelligence/7-top-tools-taming-big-data-191131?page=0,2

NoSQL goes hand in hand and here is imitation by Oracle to join the bandwagon

http://www.infoworld.com/d/data-explosion/first-look-oracle-nosql-database-179107?page=0,2

Does Ruby really get IT ?

Once upon a time, developer productivty was indeed a rational argument for choosing one language over another. When we moved from Assembly to C, for instance -- we're talking a major reduction in finger ache, let alone not having to manage the stack. When we moved from C++ to Java, not having to manage memory was huge. But the individual productivity difference from Java to Ruby is comparatively small. 


More here



http://www.javaworld.com/javaworld/jw-05-2012/120531-ruby-and-the-developer-productivity-myth.html