Which Interpreted Programming Language Offers the Best Performance for Modern Production Applications?

Choosing the best interpreted programming language for modern production applications can be a daunting task, as the concept of “best performance” is subjective and multifaceted. When considering performance, it is important to clarify the context and criteria.

Best Numerical Performance vs. Best Text Processing Performance

The term "interpreted programming language" often evokes questions related to speed and efficiency. However, the best performing language can vary significantly based on the specific application. For numerical performance, languages like LuaJIT with just-in-time (JIT) compilation can be highly effective. LuaJIT, a JIT compiler for Lua 5.1, demonstrates exceptional speed, making it a preferred choice in many game engines and real-time applications.

LuaJIT: Fast and Lean

According to performance benchmarks, LuaJIT is on average 27 times and in median 18 times faster than plain Lua. This performance is comparable to that of Java Hotspot, but with a much smaller footprint. LuaJIT is widely used in game engines due to its lightweight and efficient nature. For a comprehensive comparison, you can refer to this evaluation.

Energy Efficiency and Memory Consumption

Another aspect to consider is energy efficiency and memory consumption. A study from the Polytechnic University of Catalonia evaluated the energy consumption and memory footprint of various scripting languages. LuaJIT performed exceptionally well in this regard, making it an ideal choice for applications where these factors are critical.

Julia as an Interpreted Language

For interpreted languages with native machine code generation, Julia is a strong contender. Julia has a read-eval-print loop (REPL), making it an interpreted language, and it generates native machine code, which is faster than virtual machine-based languages like Python, Ruby, and Perl. Julia’s performance is comparable to that of compiled languages, thanks to its high-level features and efficient runtime.

Performance Metrics and Code Optimization

Performance is a vast subject in software engineering, and any answer to the question of best interpreted language depends on the specific performance metrics you care about. There are numerous factors, including the efficiency of the code, the expertise of the developer, and the context of the application.

Optimization and Expertise

Despite the performance of a language, the quality and optimization of the code written for it are crucial. Even though Java, Scala, and Clojure are compiled, they are compiled into Java bytecode run by the Java Virtual Machine (JVM). The JVM has been optimized for decades, making it a powerful choice for many applications. In my experience, both Java and Clojure have delivered incredibly fast code, handling billions of transactions efficiently.

GraalVM: Turning Interpreted Languages into Native Applications

With the advent of tools like GraalVM, the distinction between interpreted and compiled languages is blurring. GraalVM can compile many languages directly into native applications for various operating systems, making them as performant as native compiled languages. This flexibility provides developers with a choice between the advantages of scripting languages and the performance benefits of native compilation.

Conclusion

The best interpreted programming language for modern production applications is dependent on the specific requirements of the project. LuaJIT and Julia demonstrate remarkable performance in specific contexts, while Java and Clojure offer robust performance through their optimized JVM. The key takeaway is to carefully consider the performance metrics and the context in which the language will be used.