Big data programming languages are gaining in importance because they enable the mining of massive datasets, the collection of which across virtually all sectors of government, science, and commerce has become the norm.
Google's open source Go language, originally created to address the company's issues with scaling systems and concurrent programming, has had the most traction. Currently in 10th place in IEEE Spectrum's rankings, Go has risen 10 positions in only two years, mainly thanks to the large increase in related activity on the GitHub source code archive.
Also having risen significantly since 2014 is current fifth-place-holder R, which registered about 46% more questions on Stack Overflow, and increasingly is cited in scholarly research papers.
Meanwhile, there has been a decline in use of proprietary data-analysis languages such as Matlab and SAS, although usage of both languages is continuing to expand at slower rates than some of the languages that are displacing them.
Java and Python still dominate in terms of jobs, but recruiter interest in R and Scala has climbed substantially since 2014.
Still, IEEE Spectrum found about 15 times as many job listings for Python developers as for R programmers. R may offer exceptional visualization and exploratory analysis and is popular with academics writing research papers, but Python has significant benefits for users in production environments.
From IEEE Spectrum
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