  Research in high energy physics (HEP) requires huge amounts of computing and
storage, putting strong constraints on the code speed and resource usage. To
meet these requirements, a compiled high-performance language is typically
used; while for physicists, who focus on the application when developing the
code, better research productivity pleads for a high-level programming
language. A popular approach consists of combining Python, used for the
high-level interface, and C++, used for the computing intensive part of the
code. A more convenient and efficient approach would be to use a language that
provides both high-level programming and high-performance. The Julia
programming language, developed at MIT especially to allow the use of a single
language in research activities, has followed this path. In this paper the
applicability of using the Julia language for HEP research is explored,
covering the different aspects that are important for HEP code development:
runtime performance, handling of large projects, interface with legacy code,
distributed computing, training, and ease of programming. The study shows that
the HEP community would benefit from a large scale adoption of this programming
language. The HEP-specific foundation libraries that would need to be
consolidated are identified
