Another lesser-known but powerful feature is Julia's support for metaprogramming. Through the use of macros, developers can generate and manipulate code at compile-time, enabling advanced code transformations and optimizations.

Julia also has native support for distributed computing, making it ideal for parallel and distributed computing tasks. The built-in Distributed module allows developers to easily work with multiple processes and distribute workloads across a cluster of machines.

In addition, Julia provides seamless integration with other popular programming languages like Python, R, and C. This interoperability enables developers to leverage existing libraries and tools from these languages within their Julia codebase.

Julia's multiple dispatch feature is another interesting aspect. It allows functions to be defined for specific combinations of argument types, enabling highly flexible and efficient code. This feature sets Julia apart from many other dynamic programming languages.

One lesser-known feature is Julia's ability to call C and Fortran functions directly without any wrappers or bindings. This allows developers to easily interface with existing codebases in these languages and leverage their performance benefits.