Julia vs. SQL vs. Scala vs. python-sql Comparison Chart

Julia was designed from the beginning for high performance. Julia programs compile to efficient native code for multiple platforms via LLVM. Julia uses multiple dispatch as a paradigm, making it easy to express many object-oriented and functional programming patterns. The talk on the Unreasonable Effectiveness of Multiple Dispatch explains why it works so well. Julia is dynamically typed, feels like a scripting language, and has good support for interactive use. Julia provides asynchronous I/O, metaprogramming, debugging, logging, profiling, a package manager, and more. One can build entire Applications and Microservices in Julia. Julia is an open source project with over 1,000 contributors. It is made available under the MIT license.

Scala combines object-oriented and functional programming in one concise, high-level language. Scala's static types help avoid bugs in complex applications, and its JVM and JavaScript runtimes let you build high-performance systems with easy access to huge ecosystems of libraries. The Scala compiler is smart about static types. Most of the time, you need not tell it the types of your variables. Instead, its powerful type inference will figure them out for you. In Scala, case classes are used to represent structural data types. They implicitly equip the class with meaningful toString, equals and hashCode methods, as well as the ability to be deconstructed with pattern matching. In Scala, functions are values, and can be defined as anonymous functions with a concise syntax.