Eight programming languages on the rise

Programming languages on the rise: Matlab

Built for mathematicians to solve systems of linear equations, Matlab has found rising interest in the enterprise, thanks to the large volumes of data today's organisations need to analyse. Many of the more sophisticated statistical techniques that match people with advertisements, songs or web pages depend upon the power of algorithms like those solved by Matlab.

Expect Matlab use to grow as log files grow fatter. It's one thing for a human to look at the list of top pages viewed, but it takes a statistical powerhouse to squeeze ideas from a complex set of paths. Are people more likely to shop for clothes on Monday or Friday? Is there any correlation between product failures and the line that produced them?

MathWorks, the company behind Matlab, offers a diverse set of whitepapers showing how engineers are searching for statistical answers. Toyota Racing, for instance, plans its NASCAR entries by analysing tests in wind tunnels and other labs. Canada's Institute for Biodiagnostics is searching for the best treatment for burns.

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 serverside. 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, revitalising the ancient dream of bringing harmony to both client and serverside 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.

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. Analysing weather patterns to find the best places to build wind-powered generators is one example.