Over the last few years, we’ve been using Scala to build data pipelines, stream processing, and many other applications; at the same time, we’ve been hearing many positive things about Rust. This article aims to provide a comprehensive comparison between both languages, no matter what their role is.
An overview of Scala
Scala was the first language developed by scholars to run on the Java Virtual Machine as an alternative to Java. In Scala, you get the benefits of both functional and object-oriented programming.
Like Scheme, Standard ML, and Haskell, Scala has many functional programming features, such as currying, type inference, immutability, lazy evaluation, and pattern matching. Java compatibility issues still exist with this powerful but difficult-to-learn language.
You can express any kind of problem in Scala in a very different way than you can in Java or Go. Besides being compatible with Java, it comes with all the optimizations built into the JVM over the years. There are tons of features included in the type system, including building custom DSLs for your libraries, enforcing checks at compile time, etc.
It is difficult to master and learn. In a large project, maintaining code consistency is difficult. There are some compatibility issues with Java, and if you need Java libraries, Scala loses its advantages. Due to its large container size and difficulty in tuning, it inherits the JVM issues for cloud-native applications.
An overview of Rust
Originally developed at Mozilla in 2006, Rust achieved its first stable release in 2015. Designed for performance and safety, Rust is a general-purpose programming language that supports multiple paradigms.
Many companies have been using it over the last 5 years, including Amazon Web Services, Microsoft, Facebook, Mozilla, Dropbox, and Cloudflare. There is no garbage collection in Rust, and reference counting is optional. To maintain the same level of performance, Rust was originally developed to replace C++.
It is extremely fast and efficient. It offers a wide range of features, such as closures, pattern matching, collections, generics, etc. Easily readable and concise. A cargo package manager is an excellent tool.
It can interact with existing C programs and is compatible with C. The community behind it is thriving, and it is truly open source. Cost-effective and low energy consumption. It has grown rapidly and is becoming more popular. It handles errors very well.
Since it does not have native concurrency support, you have to use libraries to do this. Even though the number of production-grade applications is growing, there are not many currently in production. Quite a challenge to learn, especially the ownership model.
Comparison between Scala and Rust
Scala is the most suitable choice for Big Data/Data Processing. Akka is a beast of its own and can handle a large number of requests without relying on any external libraries. Besides the actor library in Rust, there is also Actix-web, one of the fastest HTTP servers on the market, beating virtually any HTTP server written in Scala.
The Scala Play Framework is best suited for stateful web applications or applications that last for a long time. As a result, the JVM has enough time to optimize the application. A systems programming language, Rust, is focused on performance, low resource usage, and low-level details. This new and simpler programming language aims to replace C++ completely.
There is some difference between Scala and Rust, but Rust is not far behind. Only some features, such as higher-order types or tail recursion checks, are missing at the moment, but they will be added shortly. WebAssembly is the major component of WebAssembly, which is supported by the Rust first class. Compared to Rust, Scala is a better choice for Big Data (Spark and Hadoop ecosystems).