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Best Programming Languages to Learn

Best Programming Languages to Learn
Hostman Team
Technical writer
Infrastructure

Anyone who decides to get into programming faces an important question: which language should they learn first? For a beginner unfamiliar with software development's nuances, trying to answer this alone can easily lead to mistakes.

Choosing hastily comes with a risk, as you might fall into the sunk cost trap. You could end up picking a language that doesn't align with your desired direction, whether it's mobile development, game dev, or systems programming. Relearning another language later may render much of your time and effort wasted.

So, it is of course much better to make the right decision early. And for this, you need at least a general understanding of how each language works: its specifics, features, areas of application.

In this article, we’ll present both complex and beginner-friendly programming languages, to help  beginners make an informed choice.

Why It’s Important to Choose the Right Programming Language

There are several reasons why it's crucial to study the features of each language at the very beginning and pick the most suitable one:

  • Task suitability. Every language has its own strengths. One might be better suited for a specific set of tasks than another. Your chosen development field heavily affects your tech stack, especially in today's world, where specialization is becoming more prominent. The days when operating systems, programs, and games were all written in one language are gone. Now, there's a tool for everything.

  • Community support. Any popular programming language has an active community, extensive documentation, and plenty of frameworks and libraries. However, more complex languages (like C++) can be harder to work with regarding libraries and documentation. You should take this into account.

  • Career prospects. Learning a high-demand language opens more job opportunities and makes it easier to find projects that align with your interests and specialization.

  • Scalability and performance. Some tasks require special features from a language, like efficient memory management or support for parallel computing. Sometimes, these factors are critical.

So, clearly understanding which language to start learning can help avoid many future issues, and at best, guide you into an exciting direction and a successful developer career.

Python: The Best Starting Point

Python is a high-level, interpreted programming language with dynamic typing.

Dynamic typing means the variable type is determined at runtime and can change. This adds flexibility but increases the chance of errors. Static typing means a variable's type is set at compile time and can't change. Type errors are caught earlier.

For example, in a dynamically typed language, you could first assign the number 7 to a variable and later assign a string like "Hello, World" to that same variable. In a statically typed language, this would cause a compile-time error.

Interpreted languages execute code directly without first converting it to machine code. Compiled languages, on the other hand, convert high-level code into machine instructions, making them generally faster.

Python was initially created by Dutch programmer Guido van Rossum in 1991. Today, it is maintained by the global Python Steering Council and the nonprofit Python Software Foundation.

Simple Syntax

Python’s key feature is its use of indentation and colons instead of curly braces to define code blocks:

if True:
	print("One block of code")
else:
	print("Another block of code")

This simplifies the language and makes the code more visually readable, especially in Object-Oriented Programming:

class Butler:
	def __init__(self, name):
		self.name = name

	def hello(self):
		print(f"The butler of this mansion welcomes you — {self.name}!")

butler = Butler("Alfred")
butler.hello()
# Output: The butler of this mansion welcomes you — Alfred

Python aims to be both clear and functional, using as few syntax elements as possible (like braces or semicolons).

Versatile Applications

Thanks to its clean syntax and line-by-line execution, Python can be used in a wide variety of fields:

  • Web Development. Building the backend of web apps, handling user requests (RESTful APIs), and generating dynamic web pages.

  • Machine Learning. Processing and analyzing large datasets, building ML models, and creating neural networks. It’s also widely used in scientific computing across physics, biology, and engineering.

  • Automation. As a scripting language, Python is used to automate routine tasks, manage servers, and streamline DevOps workflows.

Despite its power and use in large-scale infrastructure and serious applications, Python remains the most beginner-friendly programming language.

Large Community and Documentation

Python is used globally across industries and research, resulting in a massive community of developers, engineers, and scientists.

Regular conferences like PyCon, EuroPython, and PyData foster idea-sharing and collaboration.

Online platforms like StackOverflow and Reddit host extensive discussions on Python coding nuances.

The official documentation provides detailed language syntax, standard libraries, and step-by-step guides with examples, covering even the most basic topics.

JavaScript: The Language of Web Development

JavaScript is a high-level, interpreted programming language with dynamic typing. It was developed in 1995 by Brendan Eich at Netscape.

Its name's similarity to Java was a marketing decision rather than a technical one. Java was extremely popular at the time, and the name helped boost interest in the new language.

The Core of Frontend Development

Modern browsers come with a built-in JavaScript engine to run scripts that manipulate the DOM (Document Object Model) to dynamically change a web page’s content:

<!DOCTYPE html>
<html lang="en">
<head>
	<meta charset="UTF-8">
	<title>DOM Manipulation</title>
</head>
<body>
	<div id="container">
		<p>This is the original text.</p>
	</div>
	<button id="changeBtn">Change Content</button>

	<script>
		const container = document.getElementById('container');
		const button = document.getElementById('changeBtn');

		button.addEventListener('click', function() {
			const firstParagraph = container.querySelector('p');
			firstParagraph.textContent = "Text changed!";

			const newParagraph = document.createElement('p');
			newParagraph.textContent = "A new paragraph was added to the DOM.";
			container.appendChild(newParagraph);
		});
	</script>
</body>
</html>

Thanks to JavaScript, developers can create interactive UIs for modern web apps. Scripts run directly in any browser, so no extra software is needed.

This makes JavaScript one of the most accessible programming languages for beginners.

A Rich Ecosystem

Web development with JavaScript is a whole industry on its own. There are countless libraries and frameworks for managing web app states, such as React and Vue.

But JavaScript isn’t limited to the client side. With Node.js, JavaScript can also run on servers.

That's why many JavaScript applications and libraries are isomorphic, meaning they work both on the front and backend.

Because of this flexibility, JavaScript is a solid first programming language, helping you become a Full Stack developer (handling both frontend and backend).

Java: Stability and Demand

Java is a high-level, object-oriented programming language with static typing.

It was developed in 1995 by Sun Microsystems (later acquired by Oracle), led by James Gosling.

Java is a compiled language. Its source code is compiled into intermediate bytecode, which is executed by the Java Virtual Machine (JVM).

Since JVMs are implemented for different operating systems, Java code is cross-platform and can run on any OS without recompilation. That’s why Java’s slogan is: "Write once, run anywhere."

Android Development

Android is an OS with many components written in different languages. While its kernel is in C and C++, app development libraries and APIs are Java-based.

This has made Java almost synonymous with mobile development, including both apps and games.

For example, the popular game Minecraft was written in Java and, almost immediately after its PC release in 2011, was added to the Google Play Market as a mobile version for Android.

High Performance

Unlike interpreted programming languages, Java uses JIT (Just-in-Time) compilation.

When an application is run, the bytecode is dynamically compiled into machine code so that frequently used code segments are optimized on the fly.

On one hand, Java delivers higher performance than interpreted languages, such as JavaScript or Python.

On the other hand, the indirect execution of bytecode is slower than direct execution of machine instructions in compiled languages like C or C++.

Java is quite a fast language, especially considering that it runs through a virtual machine to provide strong cross-platform compatibility.

Popularity in the Corporate Environment

Cross-platform capabilities, application portability, predictable behavior, stability, and security are key reasons why many companies prefer Java.

And of course, its rich ecosystem—libraries, frameworks, and tools—all contribute to simplifying and accelerating enterprise application development, maintenance, and updating.

In contrast to Python, Java uses a strict C-like syntax:

public class Greeter {
	private String name;

	// Constructor that takes a name for greeting
	public Greeter(String name) {
		this.name = name;
	}

	// Method that prints the greeting to the console
	public void greet() {
		System.out.println("Hello, " + name + "!");
	}

	public static void main(String[] args) {
		// If a command-line argument is provided, use it as the name. Otherwise, default to "World"
		String name = (args.length > 0) ? args[0] : "World";
		Greeter greeter = new Greeter(name);
		greeter.greet();
	}
}

C#: A Windows Developer's Alternative

C# is a high-level, object-oriented programming language with static typing. However, dynamic typing is also possible using the dynamic keyword.

The C# programming language first appeared in 2002. It was created by Microsoft under the leadership of engineer Anders Hejlsberg. 

Like Java, C# code is not compiled directly into machine instructions but into an intermediate representation called CIL (Common Intermediate Language) or simply IL.

During program execution, the CIL code is converted via JIT compilation into native machine code optimized for the target platform.

Used in .NET Development and Unity

.NET is a development platform created by Microsoft for building portable applications. It can be used to develop websites, mobile apps, games, neural networks, and cloud services.

The .NET ecosystem includes:

  • Programming languages (C#, F#, VB.NET)
  • Libraries and frameworks (for databases, servers, graphics)
  • Runtimes

C# is the main language in the .NET ecosystem.

To some extent, Java and .NET can be seen as similar ecosystems. In Java, apps run on the JVM (Java Virtual Machine), while in .NET, they run on the CLR (Common Language Runtime). In both cases, code is compiled to bytecode, which is then executed on a virtual machine.

Moreover, Java and C# have syntactic similarities, as both are C-style languages.

Naturally, game development has also embraced C#. For instance, the popular Unity game engine uses C# as the primary scripting language for creating gameplay mechanics and scenarios.

Strong Microsoft Support

Microsoft plays a key role in the development of C#. This support includes the language itself, tooling, libraries, and infrastructure.

C# integrates well with other Microsoft products and is tailored to the Microsoft ecosystem, although it remains cross-platform. For example, the Visual Studio IDE is best optimized for the C# compiler.

A simple C# console application looks like this:

using System;

class Program
{
	static void Main()
	{
		Console.Write("May I have your name?: ");
		string name = Console.ReadLine();

		Console.WriteLine($"Welcome, {name}!");
	}
}

C and C++: For Systems Programming

C and C++ are compiled programming languages that are closely related. C++ is an extended, object-oriented version of the procedural C language.

C was created at Bell Labs by Dennis Ritchie in 1972, while C++ was introduced by Bjarne Stroustrup in 1983.

High Performance

Unlike Python, JavaScript, and Java, C and C++ do not require an interpreter or a virtual machine. Their code is compiled directly into processor instructions.

In other words, these languages are as close to the hardware as possible, allowing low-level control of system resources. That’s also why these languages are considered complex—manual control and lack of automation demand high programmer skill.

Memory Management

C and C++ give full control over computing resources. They do not include a garbage collector that automatically frees unused memory.

This reduces overhead but increases the risk of memory leaks.

Due to their performance and control, C and C++ are preferred for high-load computing, like OS kernels (Linux, Windows, macOS, Android), game engines (Unreal Engine), and financial systems.

In short, C and C++ remain the go-to languages when speed and efficiency are critical.

Foundation for Modern Languages

Originally developed for Unix-like OS development, C became the ancestor of many modern languages.

Its syntax is the foundation of many popular languages: C++, Java, C#, JavaScript, Go, Swift.

Example of simple C++ code using classes:

#include <iostream>
#include <string>

class Car {
private:
	std::string brand; 

public:
	Car(std::string carBrand) {
		brand = carBrand;
	}

	void showInfo() {
		std::cout << "Car brand: " << brand << std::endl;
	}
};

int main() {
	Car myCar("Toyota");
	myCar.showInfo();

	return 0;
}

Swift: For iOS Development

Swift is a modern high-level, statically typed language that is compiled into machine instructions.

Apple’s Official Language

Before Swift, Apple’s main language was Objective-C, dating back to the 1980s. Despite its power, it had outdated principles and lacked support for modern syntax and safe memory handling.

In 2014, Apple introduced Swift, a modern, safe, and convenient language aimed at improving code writing, safety, performance, and memory management.

In short, Swift was created as Apple’s new official language for iOS, macOS, watchOS, and tvOS development.

Simplified Syntax Compared to Objective-C

Objective-C:

NSString *name = @"John";
NSInteger age = 25;
NSArray *fruits = @[@"Apple", @"Banana", @"Orange"];

- (void)greet:(NSString *)name {
	NSLog(@"Hello, %@", name);
}

[self greet:@"Alice"];

Swift:

let name = "John"
var age = 25
let fruits = ["Apple", "Banana", "Orange"]

func greet(name: String) {
	print("Hello, \(name)")
}

greet(name: "Alice")

As a result, Swift has cleaner and more understandable syntax, which means faster development.

A Great Choice for Mobile Development

Swift is optimized for Apple’s custom chips. It’s the main language for developing native iOS applications and games.

Apple actively supports and develops the Swift ecosystem, and it is fully integrated into Xcode, Apple’s official IDE.

Go: A Modern Language from Google

Go, or Golang, is a high-level, statically typed programming language designed with concurrency in mind. It was developed in 2007 by Google engineers Robert Griesemer, Ken Thompson, and Rob Pike.

Google created Go to address speed, concurrency, and development convenience issues found in other languages, like:

  • C++: Powerful but complex
  • Java: Bytecode execution is slower than native
  • Python: Simple but slow due to interpretation

As a company focused on cloud services, Google made Go with server-side development in mind.

Simplicity and Minimalism

Go has automatic garbage collection, a simple syntax, and convenient abstractions, but it's not a classical OOP language.

There are no classes, no this keyword, no method/operator overloading.

Instead, Go uses structs with methods attached to them:

package main
import "fmt"

type Person struct {
	Name string
	Age  int
}

func (p Person) Greet() {
	fmt.Println("Hi, my name is", p.Name)
}

func main() {
	person := Person{Name: "Anna", Age: 35}
	person.Greet()
}

Go minimizes complexity and accelerates development by unifying syntax:

  • No classes/inheritance: use structs and interfaces instead.
  • No method/operator overloading: one name per method.
  • No exceptions: use explicit error checks

Exceptions are errors thrown by an application during execution that can be caught and handled by user-written code without terminating the program.

At first glance, such simplification may seem to limit the programmer’s capabilities. However, in reality, a strict definition of application logic provides greater flexibility in possible implementations and solutions.

This is likely why Go, along with Python and JavaScript, is considered one of the best programming languages for beginners.

High Performance

Go code is compiled to machine instructions. The lack of heavy features like overloading and exceptions makes Go programs high-performing.

The garbage collector is optimized for minimal delays.

Instead of OS level threads, Go uses goroutines—lightweight threads that use only a few kilobytes of memory and can be spawned in large numbers.

Great for Server-Side Development

Compiled code, concurrency support, and minimal syntax make Go ideal for backend development.

Built-in packages for web servers, networking, databases, and encoding (like net/http, database/sql, encoding/json) allow out-of-the-box server app development.

Which Programming Language Should You Choose First?

So. When choosing a programming language, several important factors should be taken into account:

  • Development field. In what area will you be working? Web applications, systems programming, game development? And if it’s game development, what kind? Mobile or desktop? Or maybe even console games?

  • Future tasks. The tasks you’ll face will depend on the area of development. But the type of tasks can also vary. For example, web development includes both frontend and backend. In game development, there’s engine development and gameplay mechanics creation.

  • Entry threshold. Depending on personal aptitudes and existing skills, learning a specific programming language will be different for every developer. For instance, effective use of C and C++ requires deeper computer science knowledge: understanding memory management, algorithm complexity, and mathematical computations.

The showcased languages can be compared across several key parameters:

Language

Syntax Complexity

Execution Model

Type System

Year Released

Official Site

Primary Field

Additional Knowledge

Python

Low

Interpretation

Dynamic

1991

python.org

Data Analysis

Machine Learning, Big Data

JavaScript

Low

Interpretation

Dynamic

1995

-

Web Development

Layout, Network Protocols

Java

Medium

Compilation

Static

1995

java.com

Mobile Development

Android, DevOps

C#

Medium

Compilation

Static

2002

microsoft.com

Desktop Development

.NET

C/C++

High

Compilation

Static

1972 / 1985

isocpp.org

Systems Programming

Mathematics

Swift

Medium

Compilation

Static

2014

swift.com

Mobile Development

macOS, iOS

Go

Medium

Compilation

Static

2012

go.dev

Servers, Microservices

RESTful APIs, Containerization

Learning the syntax of a specific language is best done with the help of books. 

You can clarify various details through tutorial articles and videos. And when problems arise during learning or work tasks, you can ask questions on platforms like StackOverflow.

Ultimately, the choice always comes down to personal preference. In the long run, it’s better to pursue something you are actually interested in rather than just something profitable. Otherwise, you'll just burn out.

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09 June 2025 · 6 min to read
Infrastructure

Docker Container Storage and Registries: How to Store, Manage, and Secure Your Images

Docker containerization offers many benefits, one of which is image layering, enabling fast container generation. However, containers have limitations — for instance, persistent data needs careful planning, as all data within a container is lost when it's destroyed. In this article, we’ll look at how to solve this issue using Docker’s native solution called Docker Volumes, which allows the creation of persistent Docker container storage. What Happens to Data Written Inside a Container To begin, let’s open a shell inside a container using the following command: docker run -it --rm busybox Now let’s try writing some data to the container: echo "Hostman" > /tmp/data cat /tmp/data Hostman We can see that the data is written, but where exactly? If you're familiar with Docker, you might know that images are structured like onions — layers stacked on top of each other, with the final layer finalizing the image. Each layer can only be written once and becomes read-only afterward. When a container is created, Docker adds another layer for handling write operations. Since container lifespans are limited, all data disappears once the container is gone. This can be a serious problem if the container holds valuable information. To solve this, Docker provides a solution called Docker Volumes. Let’s look at what it is and how it works. Docker Volumes Docker Volumes provide developers with persistent storage for containers. This tool decouples data from the container’s lifecycle, allowing access to container data at any time. As a result, data written inside containers remains available even after the container is destroyed, and it can be reused by other containers. This is a useful solution for sharing data between Docker containers and also enables new containers to connect to the existing storage. How Docker Volumes Work A directory is created on the server and then mounted into one or more containers. This directory is independent because it is not included in the Docker image layer structure, which allows it to bypass the read-only restriction of the image layers for containers that include such a directory. To create a volume, use the following command: docker volume create Now, let’s check its location using: docker volume inspect volume_name The volume name usually consists of a long alphanumeric string. In response, Docker will display information such as the time the volume was created and other metadata, including the Mountpoint. This line shows the path to the volume. To view the data stored in the volume, simply open the specified directory. There are also other ways to create a Docker Volume. For example, the -v option can be added directly during container startup, allowing you to create a volume on the fly: docker run -it --rm -v newdata:/data busybox Let’s break down what’s happening here: The -v argument follows a specific syntax, indicated by the colon right after the volume name (in this case, we chose a very creative name, newdata). After the colon, the mount path inside the container is specified. Now, you can write data to this path, for example: echo "Cloud" > /data/cloud Data written this way can easily be found at the mount path. As seen in the example above, the volume name is not arbitrary — it matches the name we provided using -v. However, Docker Volumes also allow for randomly generated names, which are always unique to each host. If you’re assigning names manually, make sure they are also unique. Now, run the command: docker volume ls If the volume appears in the list, it means any number of other containers can use it. To test this, you can run: docker run -it --rm -v newdata:/data busybox Then write something to the volume. Next, start another container using the exact same command and you’ll see that the data is still there and accessible — meaning it can be reused. Docker Volumes in Practice Now let’s take a look at how Docker Volumes can be used in practice. Suppose we're developing an application to collect specific types of data — let’s say football statistics. We gather this data and plan to use it later for analysis — for example, to assess players’ transfer market values or for betting predictions. Let’s call our application FootballStats. Preserving Data After Container Removal Obviously, if we don’t use Docker Volumes, all the collected statistics will simply be lost as soon as the container that stored them is destroyed. Therefore, we need to store the data in volumes so it can be reused later. To do this, we use the familiar -v option:  -v footballstats:/dir/footballstats This will allow us to store match statistics in the /dir/footballstats directory, on top of all container layers. Sharing Data Suppose the FootballStats container has already gathered a certain amount of data, and now it's time to analyze it. For instance, we might want to find out how a particular team performed in the latest national championship or how a specific player did — goals, assists, cards, etc. To do this, we can mount our volume into a new container, which we’ll call FootballStats-Analytics. The key advantage of this setup is that the new container can read the data without interfering with the original FootballStats container’s ongoing data collection. At the same time, analysis of the incoming data can be performed using defined parameters and algorithms. This information can be stored anywhere, either in the existing volume or a new one, if needed. Other Types of Mounts In addition to standard volumes, Docker Volumes also supports other types of mounts designed to solve specialized tasks: Bind Mount Bind mounts are used to attach an existing path on the host to a container. This is useful for including configuration files, datasets, or static assets from websites. To specify directories for mounting into the container, use the --mount option with the syntax <host path>:<container path>. Tmpfs Mount Tmpfs mounts serve the opposite purpose of regular Docker Volumes — they do not persist data after the container is destroyed. This can be useful for developers who perform extensive logging. In such cases, continuously writing temporary data to disk can significantly degrade system performance. The --tmpfs option creates temporary in-memory directories, avoiding constant access to the file system. Drivers Docker Volume Drivers are a powerful tool that enable flexible volume management. They allow you to specify various storage options, the most important being the storage location — which can be local or remote, even outside the physical or virtual infrastructure of the provider. This ensures that data can survive not only the destruction of the container but even the shutdown of the host itself. Conclusion So, we’ve learned how to create and manage storage using Docker Volumes. For more information on how to modify container storage in Docker, refer to the platform’s official documentation. 
09 June 2025 · 6 min to read

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