Add to that its ease of use—Julia’s syntax is straightforward and intuitive, similar to that of Python, meaning it can be used extensively for exploratory programming and data analysis.

Julia’s creators wanted to make a language that is as fast as C — but what they created is even faster. Even though Python has become easier to speed up in recent years, its performance is ...

Julia combines the functionality of quantitative environments such as R and Python with the speed of production programming languages like Java and C++ to solve bigdata and analytics-based problems.

Julia Computing also asked users what languages they'd use if it weren't for Julia and the top alternative, not surprisingly, is Python, which would be used by 73 percent of respondents.

The open-source project behind Julia, a programming language for data scientists, has revealed which languages users would shift to if they decided no longer to use Julia. Julia, a zippy ...

Julia, a high-performance dynamic language for numerical computing, and potential rival to Python for data science, has cracked the top 20 in the Tiobe index of programming language popularity for ...

Karpinski: Yes. The idea is that it should be extremely high productivity. To that end, it’s a dynamic language, so it’s relatively easy to program, and it’s got a very simple programming model.

The other language that’s worth checking out is Julia, “a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other ...

Julia is a relatively new programming language — it was formalized 13 years ago — making its rapid ascent particularly notable. TIOBE Software ranks 100 programming languages by their ...

Earlier this month, the creators of the programming language Julia launched their startup, Julia Computing LLC, to provide training, commercial support, and consulting for those who want to use ...