Over a million developers have joined DZone.

Python: The Next Big Thing in Big Data

DZone's Guide to

Python: The Next Big Thing in Big Data

R has enjoyed widespread popularity -- but Austin-based Continuum Analytics' use of Python in their open source analytics might change the big data industry.

· Big Data Zone ·
Free Resource

The Architect’s Guide to Big Data Application Performance. Get the Guide.

R has dominated the industry as the most widely used programming language and environment in big data. Started in 1993 by Ross Ithaka and Robert Gentleman at University of Auckland in New Zealand, it's enjoyed 22 years of well documented use and reliability -- but that might be about to change.

Continuum Analytics has raised $24 million in capital from General Catalyst Partners to bring Python to the forefront as the next big programming language in big data. Silicon Angle predicts that this move is all part of Python's "renaissance" period amongst data scientists. The Austin-based company uses Python in its open source Anaconda projects, including its Anaconda Server, Anaconda Cluster and Wakari Enterprise.

In a blog post on their site, co-founder and CTO Peter Wang described how their adoption of Python for analytics came out of "frustration" towards the "old, outdated, or locked-down software and systems," choosing instead to rally "around the friendly, easy-to-learn, highly productive Python programming language" -- and it's paid off. Continuum Analytics has enjoyed a huge amount of growth and their products are currently used by the likes of LinkedIn, NASA, Microsoft and Amazon (just to name a few).

Silicon Angle's Maria Deutscher attributes their success in part to their Anaconda toolkit, a "free collection of some 330 libraries that augment the core syntax of the web-oriented language with advanced functions for analyzing and visualizing large datasets."

According to an August 2014 poll, KDNuggets states that 49 percent of their audience uses R, and 35 percent use Python with 20 percent using a combination of the two. Another 30.6 percent use SQL.

Editor's Note: A previous version of this article incorrectly stated that R was developed by Microsoft. Special thanks to Mark Norrie for pointing out our mistake. Got feedback for our editors? Chat with us at editors@dzone.com.

Learn how taking a DataOps approach will help you speed up processes and increase data quality by providing streamlined analytics pipelines via automation and testing. Learn More.

big data ,python

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}