Julia

Features Rating Results
Generic Features Rating Results
Installability
0
No votes yet
Usability
0
No votes yet
Robustness
0
No votes yet
Security
0
No votes yet
Scalability
0
No votes yet
Overall Quality
0
No votes yet
Specific Features Rating Results
Functional VS Object-Oriented
0
No votes yet
Compiler VS Interpreter
0
No votes yet
Learning curve
0
No votes yet
Parallel programming
0
No votes yet
Comprehensive documents
0
No votes yet
Popularity and community support
0
No votes yet
Latest update/releases
0
No votes yet
License: 
MIT LICENSE
Description: 

Julia is fast!
Julia was designed from the beginning for high performance. Julia programs compile to efficient native code for multiple platforms via LLVM.

Dynamic
Julia is dynamically-typed, feels like a scripting language, and has good support for interactive use.

Optionally Typed
Julia has a rich language of descriptive datatypes, and type declarations can be used to clarify and solidify programs.

General
Julia uses multiple dispatch as a paradigm, making it easy to express many object-oriented and functional programming patterns. The standard library provides asynchronous I/O, process control, logging, profiling, a package manager, and more.

Technical
Julia excels at numerical computing. Its syntax is great for math, many numeric datatypes are supported, and parallelism is available out of the box. Julia's multiple dispatch is a natural fit for defining number and array-like datatypes.

Composable
Julia packages naturally work well together. Matrices of unit quantities, or data table columns of currencies and colors, just work — and with good performance.