New programming languages are gaining popularity and changing the way developers write code. Over the years, we have witnessed the evolution of established programming languages like Python, Java, and C++. Existing programming languages have served us well for decades, but as technology advances, so do our needs. Emerging programming languages aim to address specific challenges or offer innovative solutions that existing languages may not fully support.
For programmers, both seasoned and aspiring, the emergence of new programming languages is an invitation to a journey of continuous learning and exploration. Today, the mastery of multiple programming languages is no longer a luxury but a necessity. It’s akin to adding an arsenal of diverse tools to your toolkit, each uniquely suited for different tasks and challenges. In this article, we are listing some of the best rising programming languages with growing popularity.
New Rising Programming Languages:
Popularity Rating: 85/100
- Enterprise Applications: Many large enterprises prefer TypeScript for their internal and customer-facing applications due to its robustness and ability to handle large codebases effectively.
- Full-Stack Development: TypeScript’s compatibility with Node.js makes it a popular choice for full-stack development, allowing developers to use a single language across both client-side and server-side code.
- Mobile App Development: With frameworks like Ionic and React Native supporting TypeScript, it’s increasingly used in mobile app development for building cross-platform mobile applications.
- Game Development: TypeScript is also finding its way into game development, especially for web-based games, due to its performance and ability to work seamlessly with web technologies.
- Cloud Applications: TypeScript’s support for modern cloud development practices and its integration with various cloud services make it suitable for developing cloud-native applications.
- IoT Applications: TypeScript is used for developing applications that require robust front-end interfaces to interact with various IoT devices.
Popularity Rating: 80/100
Swift, a high-level, multi-paradigm programming language developed by Apple for building apps across its ecosystem, including iOS, macOS, watchOS, and tvOS. Known for its clean and expressive syntax, Swift is designed to be both powerful and easy to use. It incorporates modern features like safe programming patterns, fast performance, and strong typing, while also offering advanced features such as optional chaining, closures, and generics. Swift’s automatic memory management and error handling enhance its safety and reliability. These features, combined with its seamless integration with existing Apple frameworks and Objective-C code, make Swift a versatile and efficient choice for developers.
- iOS App Development: Swift is the primary language for developing applications for Apple’s iOS platform. It’s used to create everything from simple utility apps to complex, feature-rich mobile applications.
- macOS App Development: Developers use Swift to build applications for macOS, taking advantage of its integration with Apple’s Cocoa and Cocoa Touch frameworks.
- watchOS and tvOS Applications: Swift extends its capabilities to the development of apps for Apple Watch and Apple TV, enabling a seamless user experience across all Apple devices.
- Server-Side Programming: With its support for Linux, Swift is also used in server-side programming. Developers can build robust back-end systems and web services using Swift.
- Game Development: Swift’s performance and graphics support make it suitable for game development, particularly for iOS and macOS platforms.
- Educational Purposes: Swift Playgrounds, an iPad-exclusive app, uses Swift to teach coding in an interactive and engaging way, making it accessible for beginners and young learners.
- Cross-Platform Development: While primarily used for Apple’s ecosystem, Swift’s capabilities are being extended to other platforms, including Windows and Android, through various tools and frameworks.
- Enterprise Applications: Many businesses and organizations use Swift for their internal and customer-facing applications, leveraging its security and performance features.
- AI and Machine Learning: Swift is increasingly being used in artificial intelligence and machine learning projects, especially those that are integrated with iOS applications.
- Cloud Services and IoT: Swift’s scalability and performance make it suitable for cloud-based applications and Internet of Things (IoT) projects.
Popularity Rating: 80/100
Kotlin is swiftly becoming the go-to language for Android development. Kotlin is renowned for its concise syntax and interoperability with Java, significantly enhancing developer productivity and code maintainability. It offers robust safety features like null safety and immutability, making it a preferred choice for Android development, server-side applications, and cross-platform projects. This language’s user-friendly nature is not just attracting seasoned coders but also those new to the world of Android app development.
- Android Development: Kotlin’s most notable adoption has been in Android development. In 2019, Google declared Kotlin as its preferred language for Android app developers. The language’s compatibility with Java and its more concise syntax make it an ideal choice for modern Android applications.
- Server-Side Development: It’s increasingly used for backend development, compatible with Java-based frameworks like Spring, allowing for efficient server-side applications.
- Cross-Platform Mobile Development: Through Kotlin Multiplatform, it allows sharing business logic across iOS and Android, streamlining the development process for mobile applications.
- Data Science: Although not as prevalent, Kotlin is making strides in data science, offering a more statically typed alternative to Python for data manipulation and analysis.
- Desktop Applications: Kotlin can be used for building desktop applications, leveraging Java libraries and tools for a rich user interface and functionality.
- Native Applications: With Kotlin/Native, developers can compile Kotlin code to native binaries, which is particularly useful for creating lightweight applications for platforms like iOS and macOS.
Popularity Rating: 75/100
Rust, with its unwavering focus on safety and efficiency, is revolutionizing systems programming. Is is known for its blazing speed and memory efficiency, operates without a runtime or garbage collector. This unique trait allows Rust to power performance-critical services, run on embedded devices, and integrate seamlessly with other languages. Its unique approach to preventing segfaults and ensuring thread safety has garnered a loyal following. As developers seek more secure and reliable coding environments, Rust’s popularity is on a steady rise, reflecting a growing awareness of its capabilities.
- Command Line Applications: Rust is ideal for creating efficient and sophisticated command-line tools and interfaces.
- WebAssembly: Enhances web applications by integrating high-performance Rust modules for computationally intensive tasks.
- Networking: Offers reliable, high-performance solutions for building secure and efficient network services.
- Embedded Systems: Suitable for resource-constrained embedded devices, offering low-level control with high-level conveniences.
- Cross-Platform Development: Enables development of portable applications across various operating systems and environments.
- Game Development: Emerging in game development for building efficient game engines and gameplay programming.
- Cloud Computing: Ideal for constructing fast and secure cloud services, benefiting from Rust’s efficient concurrency.
- Machine Learning: Gaining ground in machine learning for creating high-performance models and data processing pipelines.
5. Go (Golang)
Popularity Rating: 70/100
Go, commonly known as Golang, is a modern programming language created at Google in 2007 and has since gained popularity across the software development landscape. Go is prized for its simplicity with a clean syntax, making it easy to write and maintain code, while also offering powerful concurrency support through goroutines and channels, facilitating the development of highly scalable applications. Additionally, Go boasts a strong standard library, efficient garbage collection, and cross-platform compatibility, making it an efficient choice for building performance-critical applications across various platforms.
- Cloud and Network Services: Go is extensively used in cloud computing and network services for its efficiency in handling concurrent tasks and networked systems. It’s a preferred language for developing cloud infrastructure and services.
- Web Development: Go is employed for building fast, scalable backend systems for web applications. Its standard library includes robust support for HTTP servers, making it suitable for developing RESTful APIs and microservices.
- DevOps and Site Reliability Engineering: In the field of DevOps, Go is used for creating tools for automation, monitoring, and infrastructure management. Its performance and cross-platform support are key factors in its use for developing DevOps tools.
- Command-Line Tools and Utilities: Go’s ability to compile down to a single binary across multiple platforms makes it ideal for developing portable command-line tools and utilities that are easy to distribute and deploy.
- Containerization and Orchestration Tools: Go has been instrumental in the creation of popular DevOps tools like Docker and Kubernetes, which are widely used for containerization and orchestration in software deployment.
- Distributed Systems and Databases: Go is also used in the development of distributed systems and databases, such as CockroachDB, due to its efficiency in handling large-scale data and operations.
- Static Site Generators: Hugo, a popular static site generator that prioritizes speed and flexibility, is another example of Go’s application, allowing developers to create efficient and fast-loading websites.
- IoT and Edge Computing: The lightweight nature of Go makes it suitable for IoT applications and edge computing, where resources are often limited.
Popularity Rating: 70/100
- Cross-Platform Mobile App Development: Dart is extensively used in the Flutter framework for developing high-quality, natively compiled applications for mobile platforms (iOS and Android).
- Desktop Application Development: Dart supports the development of desktop applications for macOS, Windows, and Linux, offering a unified development experience across platforms.
- Server-Side Development: Dart is also used in server-side development, thanks to its efficient performance and ability to handle asynchronous operations.
- Internet of Things (IoT): With its ability to compile to ARM and x86 architectures, Dart is becoming a viable option for IoT applications, where performance and efficiency are crucial.
- Game Development: Although not as widespread, Dart is being explored in the realm of game development, particularly for mobile and web-based games.
- Educational Purposes: Dart’s easy-to-learn syntax makes it an excellent choice for educational purposes, teaching programming concepts and application development.
Popularity Rating: 65/100
Elixir is a dynamic, functional programming language known for its scalability and maintainability. It runs on the Erlang VM, making it ideal for building low-latency, distributed, and fault-tolerant systems. Elixir’s design emphasizes concurrency and scalability, allowing it to efficiently manage resources across both single machines and distributed networks. Its approach to fault tolerance is robust, offering mechanisms to handle failures and recover gracefully.
- Web Development: Elixir is widely used for building scalable and maintainable web applications. Its concurrency model and fault-tolerance mechanisms make it an ideal choice for high-traffic web services.
- Embedded Software: The language’s lightweight processes and fault tolerance features are well-suited for reliable embedded systems and IoT applications.
- Machine Learning: Elixir’s capabilities in handling concurrency and distributed processing make it a strong contender in the field of machine learning, especially for data pipelines and numerical computations.
- Data Pipelines: Its efficient handling of large volumes of data and concurrent processing abilities make Elixir a good choice for developing data pipelines.
- Multimedia Processing: Elixir is also used in multimedia processing, where its performance in data-intensive and real-time processing tasks is highly valued.
- Financial Services: Elixir enables the development of secure and highly available trading platforms, payment gateways, and risk management systems.
Popularity Rating: 60/100
Julia is a high-level, high-performance programming language specifically designed for technical computing. It was created to address the need for a language that combines the ease of use of languages like Python with the speed and efficiency of languages like C or Fortran. Its robust support for multiple dispatch, rich ecosystem of libraries, and seamless interoperability make it a versatile choice for data-intensive applications and scientific computing. Julia maintains an accessible and user-friendly syntax also make it favorite among data scientists and researchers who require a robust tool for complex computations.
- Numerical and Technical Computing: Julia is extensively used for numerical analysis and technical computing, thanks to its high-level, high-performance computation capabilities.
- Data Science and Machine Learning: Widely used in data science and machine learning for its speed and ease of use, with libraries like Flux.jl and MLJ.jl for model development.
- Web Programming: It is used in both server-side and client-side web programming, suitable for handling various aspects of web-based applications.
- Systems Programming: Julia’s capabilities extend to low-level systems programming, demonstrating its versatility.
- Finance: Employed in finance for risk assessment, portfolio optimization, and algorithmic trading due to its quick financial calculations.
- Engineering: Engineers rely on Julia for simulations, including finite element analysis, computational fluid dynamics, and structural analysis.
- Bioinformatics: In bioinformatics, Julia is vital for tasks like DNA sequence analysis and genomics research due to its speed in processing large datasets.
- High-Performance Computing (HPC): Gaining ground in HPC for its utilization of modern processors and suitability for simulations and data processing.
- Robotics and Control Systems: Julia’s real-time capabilities make it suitable for robotics, analyzing sensor data and controlling robotic systems.
- Hardware Design and Synthesis: In hardware design, particularly for FPGA development, Julia serves as a high-level synthesis tool.
- Interoperability with Other Languages: Julia has built-in support for calling C or Fortran language libraries and can interoperate with a variety of languages, including Python, R, MATLAB, and others.
- Scientific Computing: The language is used in quantum computing, climate change modeling, and data analysis in large-scale scientific experiments like those at CERN.
- Pharmaceuticals and Drug Development: Julia is also employed in the pharmaceutical industry for drug development and other related research.
Popularity Rating: 60/100
- Web Programming: F# is utilized in web development, notably with frameworks like the SAFE Stack for full-stack web applications and WebSharper for alternative web solutions.
- Cross-platform App Development: It is employed in cross-platform app development, compatible with Xamarin for iOS and Android apps, and enhanced by the Fabulous library for functional programming.
- Analytical Programming: F# is widely adopted in quantitative finance, energy trading, machine learning, and business intelligence, leveraging its scripting capabilities and Microsoft product compatibility.
- Scripting: The language serves as an effective tool for desktop and REPL scripting, particularly valued for its flexibility and ease of use.
- Cloud Computing: F# is used in cloud computing applications, especially for writing scalable and high-performance code for cloud services. Azure Functions, for instance, support F# for serverless computing.
- Open-source Community: F# fosters a robust open-source community, with contributions to projects like Fable, Paket, FAKE, Giraffe, and Suave, enhancing its versatility and reach.
Popularity Rating: 55/100
Elm is a front-end web development language celebrated for its functional programming approach and strong type system, which greatly reduces runtime errors. It features immutable data to ensure stability and employs The Elm Architecture, an intuitive structure for applications that enhances code reusability and maintainability. Known for its helpful compiler with user-friendly error messages, Elm stands out for creating reliable web applications with a focus on eliminating runtime exceptions. This combination of features makes Elm a robust and user-friendly choice for web developers.
- Single-Page Applications (SPAs): Elm is highly suited for developing SPAs, where its features like no runtime exceptions and strong type system ensure smooth and reliable user experiences.
- Web Development: Elm is primarily used in web development, particularly for creating complex user interfaces that are robust and easy to maintain.
- Educational Tools: Due to its simplicity and ease of understanding, Elm is often used in educational settings to teach the concepts of functional programming and web development.
- Interactive Web Applications: Elm’s architecture is beneficial for building interactive web applications, where stability and performance are critical.
- Front-End Development: It is commonly used in front-end development, especially in projects where code reliability and maintainability are priorities.
Popularity Rating: 50/100
Crystal, a high-level, general-purpose object-oriented programming language designed with a syntax inspired by Ruby, it offers the elegance and productivity of a scripting language, combined with the speed, efficiency, and type safety of a compiled language. Crystal stands out for its static type-checking, which doesn’t typically require specifying the types of variables or method arguments, thanks to its advanced global type inference algorithm. This unique feature allows for a more streamlined coding experience, akin to scripting languages, while maintaining the rigor of a statically-typed language.
- Web Development: Crystal’s syntax, inspired by Ruby, makes it suitable for building web applications, especially for developers familiar with Ruby on Rails or similar frameworks.
- Backend Development: Its performance efficiency makes it a good choice for developing backend services, APIs, and server-side logic.
- Command-Line Tools: Crystal can be used to create efficient and fast command-line applications, benefiting from its compiled nature and efficient execution.
- Data Processing: Due to its high performance, Crystal is suitable for data processing tasks, where speed and efficiency are crucial.
- Network Programming: Its efficient handling of concurrency and system-level access makes Crystal a viable option for network applications and protocols.
- Embedded Systems: While not as common, Crystal’s compiled nature and efficiency could make it suitable for certain types of embedded systems programming.
Popularity Rating: 45/100
Red is a unique programming language known for its simplicity and flexibility, catering to a wide range of programming needs, from system-level tasks to high-level scripting. It stands out for its lightweight design, allowing for rapid development and deployment, and its ability to seamlessly interoperate with other languages and tools.
- System-Level Programming: Red’s ability to handle system-level tasks makes it a valuable asset in areas where close-to-the-metal control is required. Its low-level operations capability allows for efficient memory management and process control, essential in systems programming.
- High-Level Scripting: On the flip side, Red is equally adept at high-level scripting tasks. Its syntax and structure are designed to be easy to learn and use, making it suitable for rapid development and prototyping, especially in smaller projects or startups.
- GUI Development: Red has shown its strength in GUI (Graphical User Interface) development. Its toolkit allows for the creation of rich, responsive user interfaces, which can be a game-changer for desktop applications and tools.
- Data Processing: Red’s data handling capabilities, though not as extensive as languages like Python or R, are still robust enough for basic to intermediate data processing tasks. This makes it a good fit for small-scale data analysis projects.
These growing programming languages are not just alternatives to the established ones — they are carving their niches, offering unique solutions to modern programming challenges. Whether it’s enhancing performance, simplifying syntax, or offering robust data analysis capabilities, each language brings something special to the table.