There are also a number of open source alternatives, including Octave, Scilab, Sage, and PySci, one of the aforementioned Python libraries. All of these tools help with the complicated statistical analysis that is now becoming common for firms trying to understand what the customer did and what the customer may want to do in the future.
Programming languages on the rise: JavaScript
JavaScript is not an obscure language by any means. If anything, it may be the most compiled language on Earth, if only because every browser downloads the code and recompiles it every time someone loads a Web page. Despite this fact and the increasing dominance of AJAX-savvy Web pages, JavaScript is rarely thought of as a language that runs on the big iron.
This isn't for lack of trying. Netscape tried to make JavaScript the common language on its server platform back in 1996, but ended up establishing it only in the browser. Aptana, one of the latest devotees, throttled its development of Jaxer when it never caught on. AppJet, a small experimental company, used the Rhino JavaScript library written in Java to make it simpler to code server-side. That company was acquired by Google in 2009 and now seems to be devoted to other projects.
Still, new applications for JavaScript abound. CouchDB, for instance, doesn't use SQL for queries, instead taking two JavaScript functions, one for selection (Map) and the other for bundling everything together (Reduce). Node.js is one of the more exciting server-side JavaScript frameworks to appear as of late, revitalizing the ancient dream of bringing harmony to both client and server-side programming. The package takes Google's V8 JavaScript engine created for the browser and lets it make the decisions about formatting outgoing data.
Everywhere people need a small amount of scripting power, JavaScript finds new uses. One of the simplest ways for developers of large applications to offer users the ability to create subapplications, JavaScript continues to grow in the enterprise, one small chunk of code at a time.
Programming languages on the rise: R
Statistical analysis is being increasingly done in R these days, although some purists call the language S, its original name. Tibco sells a commercial version called S-Plus.
[ For an in-depth primer on what enterprises are doing with "big data," see "The big promise of Big Data: What you need to know today." ]
There probably won't be an S++ because the language is more a version of LISP or Scheme with additional features for computing statistical functions and then displaying the results in pretty pictures. If the boss wants the computer to churn through billions of lines of log files looking for patterns, clusters, and predictive variables, R or S is a well-loved solution.
R is another Swiss Army Knife of numerical and statistical routines for hacking through the big data sets -- collections big enough that it might be better called a Swiss Army Machete. Lou Bajuk-Yorgan, senior director of product management for Tibco's Spotfire S-Plus, says its software is used by a number of clients who are studying how business or engineering projects might work or why they fail to work. Analyzing weather patterns to find the best places to build wind-powered generators is one example.