Scala vs Java: Which Programming Language Should You Choose?

Scala vs Java: which is better? It’s a common question that developers face.

The 2024 Stack Overflow Developer Survey, which measures the popularity of different programming languages, among other things, brings interesting insights to light. While Java enjoys a significant share of 30.3%, Scala stands at 2.6%.

Whether you're a seasoned developer or just starting, understanding the nuances between these two languages can be crucial for your career and the success of your projects. Both languages are powerful and versatile, but they cater to different needs.

This guide is all about exploring the differences between Scala and Java, starting from the basics. So, let’s dive into what sets them apart and how to utilize their strengths effectively.

What is Java programming language?

Java, a language that needs little introduction, has been the backbone of enterprise applications for over two decades. It is a class-based, object-oriented programming language that emphasizes portability across platforms. Its "write once, run anywhere" (WORA) philosophy has made it a go-to language for building cross-platform applications.

Key features of Java

Here are some of the most prominent features that Java is popular for:

Object-oriented programming (OOP): Java is inherently object-oriented, making it easier to manage and maintain code by encapsulating data and behavior.

Platform independence: Java bytecode can run on any device equipped with a Java Virtual Machine (JVM), ensuring broad compatibility.

Robust memory management: Its automatic garbage collection minimizes memory leaks and optimizes application performance.

Security: It provides a secure environment with its built-in security features, including bytecode verification and runtime security checks.

Rich API: It offers an extensive library of APIs, covering everything from data structures to networking, making it easier to build complex applications.

Common use cases of Java

Java is a preferred choice across various domains in software development. Here’s a detailed look at some of its most common use cases.

Enterprise applications

Java has been the cornerstone of enterprise application development for decades. Its robustness, scalability, and security features make it the ideal choice for building large-scale, mission-critical systems.

Java’s extensive ecosystem allows developers to create complex, multi-tiered applications that can handle thousands of concurrent users. Additionally, Java’s strong typing and comprehensive error-checking capabilities reduce the likelihood of runtime errors.

Android development

When it comes to Android app development, Java has been the dominant language since the inception of the Android platform. Although Kotlin has emerged as a strong alternative, Java remains deeply integrated into the Android development ecosystem.

The Android SDK (Software Development Kit) is primarily based on Java, and a vast majority of Android apps are still written in Java. Java’s portability and extensive APIs make it easier for developers to create feature-rich applications that can run on millions of devices worldwide.

Big data

Java is a key player in big data technologies. Tools like Apache Hadoop and Apache Kafka, which are widely used for processing and managing large volumes of data, are built using Java.

Java’s performance and scalability make it well-suited for handling the distributed processing and real-time data streaming required in big data applications. Java's strong typing and concurrency features also contribute to its effectiveness in managing complex data workflows and ensuring data integrity.

What is Scala programming language?

Scala, short for "Scalable Language," was first released in 2003. Scala runs on the JVM and is designed to be a concise, elegant, and powerful language that integrates both functional and object-oriented programming paradigms.

Scala's syntax is more concise than Java's, often requiring fewer lines of code to achieve the same functionality, which can lead to increased productivity and readability.

Key features of Scala

Let’s explore the core features that make Scala a powerful and expressive language.

Functional programming: Scala supports functional programming features like higher-order functions, immutability, and pattern matching, making it easier to write clean, concise, and bug-free code.

Interoperability with Java: It can seamlessly interoperate with Java, allowing developers to use Java libraries and frameworks within Scala code.

Type inference: Its powerful type inference system reduces the need to explicitly declare variable types, leading to more concise code.

Immutable collections: Its standard library emphasizes immutable collections, which are safer to use in concurrent programming environments.

Pattern matching: Pattern matching in Scala provides a more powerful and expressive way to handle conditional logic compared to traditional if-else statements.

Concurrency: Scala's Akka framework simplifies the development of concurrent and distributed systems, making it a good choice for building high-performance, scalable applications.

Common use cases of Scala

Below, we explore some of the major use cases where Scala’s unique features and capabilities come into play.

Big data processing

Scala is the preferred language for Apache Spark, a powerful big data processing framework known for its speed and ease of use. Spark’s ability to handle large-scale data processing tasks in a distributed environment is greatly enhanced by Scala’s concise syntax and functional programming features. Its immutability and higher-order functions allow developers to write parallel and distributed processing logic with fewer errors and more clarity.

Data science and machine learning

Scala’s strong type system, along with its support for functional programming, makes it well-suited for data science and machine learning tasks. Its ability to handle large datasets, combined with its support for parallel processing, makes it an excellent candidate for developing data pipelines, performing complex data transformations, and implementing advanced machine learning models.

Reactive systems

These systems need to perform reliably under varying loads and recover gracefully from failures.

Scala’s integration with the Akka toolkit makes it an excellent choice for developing reactive systems. Akka’s implementation of the Actor model, combined with Scala’s functional programming features, allows developers to build systems that can scale horizontally across multiple nodes and handle billions of messages per second.

Scala vs Java: Important differences to know

Now that we’ve established the strengths of both Java and Scala, let's dive into a detailed comparison to help you understand where each language shines and where it might fall short.

Programming paradigms: Object-Oriented vs. Functional Programming

Java

Java is primarily an object-oriented language. You’re likely familiar with concepts like classes, objects, inheritance, and polymorphism. Java does support some functional programming features, like lambdas introduced in Java 8, but its core is still deeply rooted in OOP. This paradigm is great for modeling real-world entities and structuring large, complex systems, but it can sometimes lead to verbose code.

Scala

Scala, on the other hand, is a hybrid language that fully embraces both object-oriented and functional programming. This means you can write purely functional code with immutability and higher-order functions, or you can stick to object-oriented principles—or even better, combine both! This flexibility allows you to choose the best tool for the job, making your code more concise, expressive, and easier to reason about.

Syntax conciseness and expressiveness

Java

As mentioned above, Java’s syntax is known for being verbose. Writing even simple operations can require several lines of code. While this verbosity can make the code more explicit, it also means you spend more time writing boilerplate code, which can slow down development.

Scala

Scala’s syntax is much more concise and expressive. Thanks to features like type inference, you don’t need to declare types explicitly everywhere. Additionally, functional programming constructs like map, filter, and reduce allow you to perform complex operations on collections with just a few lines of code.

Type system

Java

Java has a relatively straightforward type system. It’s statically typed, which helps catch errors at compile time, but it doesn’t offer some of the more advanced features found in Scala. Java’s type system is easy to understand, making it accessible, but it can feel limiting when you need more flexibility.

Scala

Scala’s type system is both strong and expressive. It supports advanced features like type inference, generics, and higher-kinded types. This means you can write more abstract and reusable code. While this power can lead to more complex code, it also allows you to express more sophisticated logic without compromising type safety. In short, Scala's type system can help you write more robust and flexible code, but it does require a deeper understanding.

Learning curve: Accessibility vs depth

Java

Java is often praised for its relatively gentle learning curve, particularly for beginners in programming. Its syntax is straightforward, and its object-oriented principles are easy to grasp.

The extensive documentation and widespread community support make it easier to find resources and get help. For developers new to programming, Java provides a solid foundation that is both accessible and powerful.

Scala

Scala, while powerful, comes with a steeper learning curve. Its rich feature set, particularly its advanced type system and functional programming constructs, can be challenging for developers who are new to these concepts.

However, once you get past the initial learning phase, Scala’s expressiveness and flexibility can lead to more productive coding. While it may take longer to become proficient in Scala compared to Java, the payoff is a language that can handle complex tasks with elegance and efficiency.

Adoption and industry use

Java

Java’s adoption is widespread across a variety of industries, particularly in large enterprises where scalability, security, and stability are crucial. Java is often the language of choice for building large-scale enterprise applications, financial systems, and Android applications.

Its long history and proven track record make it a trusted platform for mission-critical systems. You’ll find Java in everything from web applications and back-end services to embedded systems and mobile apps.

Scala

Scala’s adoption, while not as widespread as Java’s, is growing rapidly in specialized domains like big data and real-time systems. Companies that need to process large volumes of data or build highly responsive, distributed applications often turn to Scala.

Additionally, Scala is often chosen by tech startups and companies that prioritize cutting-edge technology and developer productivity. If you’re working in industries that demand high concurrency, fault tolerance, and real-time data processing, Scala is a noteworthy contender.

Performance: Similar, but depends on how you use it

Java

Java is well-known for its reliable and consistent performance. It runs on the Java Virtual Machine (JVM), which is highly optimized and does a great job of managing memory and improving speed through techniques like Just-In-Time (JIT) compilation.

For most applications, Java's performance is more than enough, especially when you need something that just works well without much tweaking. However, Java’s code can be a bit wordy, which might result in slightly bulkier programs.

Scala

Scala also runs on the JVM, so it benefits from the same speed and efficiency as Java. However, Scala allows you to write more concise and expressive code, which can sometimes mean that your program runs faster because there’s less code to execute.

On the flip side, Scala has some advanced features, like lazy evaluation, which can slow things down if you’re not careful about how you use them.

In general, if you use Scala’s features wisely, you can achieve performance that’s just as good as, or sometimes better than, Java. But it’s important to understand Scala’s unique features to avoid accidentally introducing slowdowns.

Choosing between Java and Scala: How to make the right decision

When choosing between Scala and Java, it’s essential to consider several factors that align with your project goals and long-term maintenance plans.

First and foremost, think about the nature of the project you’re working on. If your project heavily relies on complex data transformations, parallel processing, or requires a high degree of scalability, Scala might be the better choice. However, if your project is more straightforward, or if you’re working within an enterprise environment where stability and a vast ecosystem are paramount, Java might be more suitable.

Another critical factor to consider is the existing codebase and infrastructure. If your project involves integrating with legacy systems or existing Java applications, Java’s compatibility and the vast array of supporting tools might give it an edge. Scala does interoperate seamlessly with Java, but the complexity of managing a mixed codebase can introduce additional overhead.

Finally, think about long-term maintainability. Scala’s expressiveness allows for very concise and powerful code, but this can sometimes come at the cost of readability, especially for developers who are not deeply familiar with the language. On the other hand, Java’s verbosity is often seen as a drawback, but it can make the code easier to understand for a broader audience, which can be crucial for projects that will be maintained over many years by different teams.

Choosing between Java and Scala ultimately depends on your specific needs and preferences as a developer. Java's simplicity and thriving ecosystem make it a reliable choice for many traditional applications, while Scala’s advanced features and functional programming capabilities offer powerful tools for tackling complex, modern challenges.

One of Scala's major strengths is its smooth interoperability with Java. This means you can easily use Scala in Java projects, leveraging Scala’s expressive syntax and functional programming features while still utilizing your existing Java code and libraries. This flexibility allows for a gradual adoption of Scala or even a hybrid approach where both languages coexist within the same project.

So, when thinking about Scala vs Java, it all comes down to understanding the strengths and trade-offs of each language in order to make an informed decision.

Frequently asked questions

Is Scala going to replace Java?

Scala is not likely to replace Java. It is more of a complementary language, often used alongside Java, particularly in specific domains like data processing.

Which is better Java or Scala?

Neither language is inherently better; the choice depends on your project needs. Java excels in enterprise applications with its robust ecosystem and widespread use. Scala offers more powerful features, making it ideal for complex data processing tasks. Choose based on your project’s requirements.

Should I learn Scala or Java for data engineering?

For data engineering, Scala is often preferred due to its powerful functional programming features and its role in popular frameworks like Apache Spark. However, learning Java first can provide a solid foundation. Ultimately, both languages are valuable, but Scala may offer more specialized tools for data engineering.

Is it easy to learn Scala?

Scala is considered more challenging to learn than Java due to its complex features. However, if you have a solid understanding of Java or other programming languages, Scala’s learning curve can be manageable with time and practice.

Is Scala dead?

No, Scala is not dead. While it’s less popular than some other languages, Scala remains actively used, especially in data processing, distributed systems, and with frameworks like Apache Spark. The language continues to evolve, and it has a dedicated community that keeps it relevant in specific domains.