This article by a seasoned software engineer and tech enthusiast Alex Babin (shared here with his permission). *** Coding languages play a vital role in shaping the manner we create software. Throughout the years, we have observed the prevalence of established languages such as Python, Java, and C++. Nevertheless, today, a fresh wave of coding languages has emerged, presenting inventive solutions and pushing the limits of what can be accomplished in the realm of software engineering. In this article, I will explore some of these newly emerged programming languages you might have not heard of yet, uncovering their potential and unique characteristics. I’ll touch upon their scope and the problems they excel at solving and also include some code samples. Let’s start!\ Pony Pony is a contemporary, statically classified, object-oriented coding language that highlights straightforwardness, efficiency, and actor-based parallelism. It provides developers with a safe and efficient environment for building highly concurrent and scalable applications. With Pony, developers can write code without the common pitfalls of deadlocks and data races, as its type system ensures memory safety and eliminates the need for manual locking. Pony also introduces "reference capabilities," which label data based on how it can be shared. However, Pony’s novelty means fewer resources and a smaller community for support. The unique syntax and semantics can be difficult for newcomers, and its standard library is not as comprehensive as those in more established languages, demanding more development from scratch. Scope: The Pony programming language is tailored to create high-performance, concurrent, and secure applications. It is especially fitting for crafting scalable and resilient systems, such as distributed and real-time applications, where concurrency and data integrity are of utmost importance. : concurrent programming Primary niche : Especially good for developing Safety-critical systems, such as medical devices, aviation software, and autonomous vehicles High-speed networking applications, including servers, routers, and real-time communication systems Interactive entertainment and multimedia applications that demand rapid response times and optimal utilization of system resources Pros and Cons: Pros Cons Exceptional concurrency support Limited adoption and community Focus on safety Small standard library Impressive performance capabilities Steep learning curve Code sample: Crystal Crystal is a compiled language that embraces static typing, fusing the inherent expressiveness reminiscent of Ruby with the inherent performance capabilities akin to languages such as C and C++. Crystal offers a familiar and readable programming style, making it a great choice for developers coming from a Ruby background. Crystal's static type checking ensures type safety and improves performance, resulting in faster execution. It also provides powerful metaprogramming capabilities that allow developers to define custom macros and enhance code expressiveness. When it comes to downsides, Crystal isn't yet as feature-rich as more established languages. Further, the compilation time can be quite long, which might deter some developers. : Scope Crystal's emphasis on web development renders it an optimal selection for designing high-velocity web applications, web services, and APIs. : web development Primary niche :\ Especially good for developing Scalable and high-performance web applications Automation scripts, command-line tools, and DevOps-related tasks Networking applications like TCP/UDP servers, proxies, and network protocols Pros and Cons: Pros Cons Ruby-like syntax Limited library support and tooling High performance Less mature ecosystem Easy to read and write code Longer compilation time Code sample: Zig Zig is a versatile, statically typed coding language that prioritizes efficiency, safeguarding, and comprehensibility. It strives to offer fine-grained authority while upholding user-friendliness and reliability. Zig's structure, influenced by the C programming language, renders it accessible to programmers well-versed in C or C++. One of Zig's key strengths lies in its predictable memory management, which includes features like automatic memory deallocation and compile-time memory tracking. Its blend of low-level control and modern language features makes Zig a compelling option for developers seeking performance and reliability in their projects. However, Zig is still in the early stages of development which means potential instability. Its community is small and the tooling is still under development. Also, the language does not yet offer a comprehensive standard library, which can necessitate extra work for programmers. : Scope Zig's interoperability with C codebases enables easy integration with existing projects, making it a powerful choice for systems programming, embedded systems, game development, and scripting. : systems programming Primary niche :\ Especially good for developing Low-level code, device drivers, operating systems, and embedded systems High-performance game engines, rendering pipelines, and game logic Efficient code for IoT and resource-constrained devices, such as sensors, microcontrollers, and wearable devices : Pros and Cons Pros Cons Excellent low-level control over code Relatively new and evolving Emphasis on safety and reliability Limited library support Good interoperability with other languages Steep learning curve Code sample: Reason Reason is an innovative statically-typed programming language that seamlessly melds the functional programming paradigm with the widely recognized syntax of JavaScript. Born out of Facebook's creative endeavors, Reason seeks to present a steadfast and dependable substitute to JavaScript for crafting web and mobile applications. The core ambition of Reason lies in fostering predictability and circumventing typical errors by leveraging static typing and strong type inference. Reason's functional programming roots provide a rich set of features for building scalable and maintainable applications. It endorses immutable data structures, pattern matching, algebraic data types, and higher-order functions, enabling more expressive and fluid code. Reason is relatively new, resulting in a small user base and fewer resources for learning and problem-solving. Its interoperability with JavaScript is a key feature, but there can be complexities and inefficiencies in this interoperation which could be a source of confusion or performance issues. : Scope Reason finds applications in various domains, including web development, mobile app development, and backend development. It is particularly well-suited for complex applications that require strong typing, concurrency, and reliability. : front-end development Primary niche : Especially good for developing Cross-platform mobile applications Compilers, static analyzers, and other development tools Scalable and maintainable web applications in finance and healthcare\ : Pros and Cons Pros Cons Strong type inference Smaller community compared to other languages Interoperability with JavaScript Limited industry adoption Functional programming features Limited tooling integration Code sample: Vlang V emerges as a contemporary programming language that was designed with a focus on developer productivity and aims to eliminate common pitfalls found in other programming languages. One of the key features of V is its simplicity. The syntax is designed to be straightforward and easy to understand, reducing the cognitive load on developers. It takes inspiration from C and Go, resulting in a familiar and intuitive programming model. V emphasizes strong type checking and automatic memory management, reducing the occurrence of bugs and memory-related issues. The language encourages explicit error handling and offers built-in support for concurrency and parallelism, making it suitable for building concurrent and high-performance applications. The language also focuses on minimizing resource usage. Vlang's simplicity and performance are promising, but its novelty results in a lack of comprehensive libraries and the small community. The language is also under constant changes which may cause instability and compatibility issues. : Scope V supports both server-side and client-side development, making it suitable for building web applications, APIs, and command-line tools. Additionally, its interoperability with existing C code allows seamless integration with libraries and frameworks. : systems programming Primary niche : Especially good for developing Operating systems, device drivers, embedded systems, and other software that interacts closely with hardware Web applications, APIs, and backend services Applications that have compatibility across various operating systems, including but not limited to Windows, macOS, Linux, etc. : Pros and Cons Pros Cons Simplicity Limited library support Safety Smaller community Fast compilation speed Immaturity of the language Code sample: Julia Julia stands as a high-level programming language crafted explicitly for numerical and scientific computation endeavors, in the realms like data analysis, machine learning, simulation, and visualization. It combines the user-friendly nature and syntax of Python with the efficiency inherent to low-level languages such as C and Fortran. A noteworthy facet within Julia's arsenal rests in its just-in-time (JIT) compilation, affording the capacity to dynamically compile code for streamlined execution. Additionally, Julia supports concurrent and distributed computing, empowering users to make use of multiple cores or even clusters of machines for speedier execution. While Julia performs well in scientific computing and data analysis, it is less versatile in other areas. Its syntax can be unfamiliar to those accustomed to languages in the C family, and although it has a growing community, it's still not as large as those of Python or R. : Scope Julia strives to strike a balance between productivity and performance, positioning it as a compelling option for data scientists, researchers, and engineers engaged in computationally demanding undertakings. : data science Primary niche r: Especially good fo Data analysis tasks, including data cleaning, processing, and statistical analysis Training and deploying complex machine learning algorithms Developing data-intensive applications and computationally intensive tasks that can benefit from parallelization \ Pros and Cons**: Pros Cons Extensive libraries and tools specifically designed for data science Steep learning curve for beginners High-performance Limited application scope Ease of use Inefficient memory management Code sample: Final thoughts These are merely a handful of examples illustrating the manifold programming languages that have surfaced in recent years. Trying out some of them can be a rewarding experience, allowing us to think differently, challenge traditional approaches, and enhance our programming skills. I personally find it immensely practical to monitor the programming languages landscape and am happy to share my findings with you.

This story contains new, firsthand information uncovered by the writer.

5 Lifehacks to Improve the Quality and Uniqueness of Your Content

New Spiral Cycle: Why Microservices Are Overrated

Nominated for 2022 - HackerNoon Contributor of the Year - Future

Nominated for 2022 - HackerNoon Contributor of the Year - Game Development

The New Wave of Programming Languages: Pony, Zig, Crystal, Vlang, and Julia

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

‘2013 Vs 2018’: The Top 10 Cryptocurrencies Five Years Ago And Today

0–100 in Django: Starting an app the right way

The Noonification: How to Deal With Flapping or Broken Tests (11/29/2023)

The Noonification: OpenAI is Sam Altman; Sam Altman is OpenAI (11/30/2023)

The Noonification: Panda Power (11/28/2023)

The Noonification: Feature Optimization for Price Prediction (11/26/2023)

‘2013 Vs 2018’: The Top 10 Cryptocurrencies Five Years Ago And Today

0–100 in Django: Starting an app the right way

The Noonification: How to Deal With Flapping or Broken Tests (11/29/2023)

The Noonification: OpenAI is Sam Altman; Sam Altman is OpenAI (11/30/2023)

The Noonification: Panda Power (11/28/2023)

The Noonification: Feature Optimization for Price Prediction (11/26/2023)

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps