Although not immediately obvious, C++ is used in Big Data along with Java, MapReduce, Python, and Scala. For example, if you’re using a Hadoop framework, it will be implemented in Java, but MapReduce ...

Typically, these Python prototypes must be rewritten for production deployment using lower-level languages like C/C++. While this produces high-performance code, it can incur considerable costs ...

In winning the designation for 2020, Python jumped 2.01 percentage points last year in the Tiobe Index of language popularity, edging out C++, which increased 1.99 percentage points.

“Python is a very easy language to learn for non-programmers,” said Peter Wang, president of Continuum Analytics. That’s important because most big-data analysts will probably not be ...

The Python community wanted a more Pythonic way to scale their code while also reducing the complexity of shifting code from a single machine to distributed environments. This demand has seen the ...

However, Python’s methods for parallelizing operations often require data to be serialized and deserialized between threads or nodes, while Julia’s parallelization is more refined.

Bodo.ai, a parallel compute platform for data workloads, is developing a compiler to make Python portable and efficient across multiple hardware platforms.It announced Wednesday a $14 million ...

C++, Go, Rust and cybersecurity shine in O'Reilly Media's analysis, but Python, Java and Javascript still rule.

“Python is a very easy language to learn for non-programmers,” said Peter Wang, president of Continuum Analytics. That’s important because most big-data analysts will probably not be ...