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This article mainly explains "what are the differences between programming languages such as Go and Scala". The content in the article is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn what are the differences between Go and Scala programming languages.

Programming languages are crucial to the pursuit of a successful career in data science. Learn more about popular languages-Go and Scala-here.

Programming languages allow professionals to do less code work, which is easier to understand. It can help big data professionals organize their unstructured datasets. Similarly, the professional who uses the code is not always the person who created the code. Therefore, writing code should be more communicative to avoid obstacles in delivering data science projects.

Needless to say, programming skills are one of the necessary skills for big data professionals. Depending on the task at hand, you want to take your knowledge to a new level, and the way your organization uses data science and the effectiveness of programming languages must be adjusted.

Among many programming languages (such as Python,Scala,Go,JavaScript,R,SQL, etc.), we chose two main languages, Scala and Go, to discuss.

Professionals choose one of the two according to the project and the customer's requirements and specifications. Golang or Go, developed by Google, is a statically typed and compiled language. These tools, source code, and compilers are free and open source. On the other hand, Scala is a general programming language that provides support for functional programming.

It is a programming language developed by Rob Pike,Robert Griesemer and Ken Thompson. The syntax of the Go language is somewhat similar to that of C and provides dynamic typing, garbage collection, type safety, variable-length arrays, and key-value mapping.

The function of Go language

Important features of Go programming include:

The program is simple and clear.

Faster compile time

Support environment adoption model

Built-in concurrency support-such as lightweight processes, channels, and select statements

Support for type embedding and interfaces

Generate statically linked native binaries without any external dependencies

Advantages of Go language

Programming languages have obvious advantages. To give just a few examples, they are:

Improved availability and service reliability because it is faster than languages that include Python and Java

It is easy for professionals with knowledge of Java or C # because it has the same process approach

It is scalable because it uses only 2KB memory when running multiple concurrent processes. It can also run efficiently without causing the system to crash.

Because Golang is powerful open source and easy to learn, organizations rely more on Golang.

Use cases for the Go language

Golang benefits enterprises in all industries. Some use cases are briefly introduced here.

Dropbox is a cloud storage sharing service that effectively manages more than 500 million users on its network through Golang.

For network, cloud and distributed functions such as Web servers, API and Web applications.

Used to build the cornerstone of local cloud computing, such as Kubernetes and Docker.

Replace the traditional similar products. For example, Teleport is the new version of the SSH server.

Suitable for creating tools and utilities because they can be quickly launched and packaged for redistribution.

With this, let's go into another one, Scala.

Scala as a programming language

Scala (Scalable language) is a multi-paradigm programming language created by Martin Odersky that can be easily integrated with functional and object-oriented languages. This is easy for professionals in data science because it is based on Java and every data science professional knows Java,C,C + + or Python. It provides a further improvement for their career in data science.

The function of Scala

Scala is extensible, object-oriented, and statically typed.

Scala is functional because each function is a value and each value is an object.

Abstractions are used consistently and securely.

Scala is extensible, so it's easy to add new languages smoothly.

Java and Scala run on a common execution platform, the Java Virtual Machine (JVM).

Scala helps you write code in a constant way, making it easy to apply parallelism and concurrency.

Advantages of Scala

Some of the advantages of using Scala include:

Provide a convenient learning experience.

Provides optimization of code complexity.

Perform Java-like functions, but use fewer lines of code.

Interoperable and compatible with Java.

Use case for Scala

Scala is also useful for novice developers and experts. Some use cases are:

It is the first choice for data engineers to use it in big data and analysis.

Because of its scalability advantage, it can be used in transaction services and concurrent systems.

Acts as a highly parallel Web framework for building API and applications.

Create highly decentralized applications within a single application.

Build libraries and frameworks based on domains.

If you choose either of these two approaches, we recommend that Go be cost-effective for cloud-native applications. For big data and concurrent critical systems, Scala seems to be the best choice. However, it all depends on the customer project you are working on. Therefore, as a data science professional, it is recommended to acquire technical skills by holding a relevant degree, obtaining big data certification, learning multiple programming languages, and excelling in soft and communication skills.

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