Programming languages are constantly evolving to meet the changing needs of developers and the growth of technology. While languages like Java, Python, and JavaScript continue to dominate, new languages are emerging that aim to fix common problems, provide better performance, and improve productivity.
I‘ve researched some of the most promising new languages that are gaining traction and have the potential to become mainstream choices in the future. Here are 12 new programming languages you should know.
1. Julia
Julia is a high-performance dynamic programming language designed specifically for scientific computing and data science. Released in 2012 by a group of researchers from MIT, Julia aims to combine the user-friendliness of Python with the speed and performance of languages like C/C++.
Some key features of Julia include:
- Optional typing – Supports both dynamic and static typing.
- High performance – Thanks to just-in-time (JIT) compilation to optimized native code. Benchmarks show it matches or exceeds C and Java speeds.
- Mathematical syntax – Uses familiar mathematical notation like MATLAB, making it easy to express computational algorithms.
- Multi-paradigm – Supports procedural, functional, and object-oriented programming styles.
- Built-in package manager – Comes with a built-in package manager for installing various libraries and dependencies.
With strong support for parallelism and distributed computing, Julia makes it easy to scale data science and numerical applications across multiple CPU cores and clusters without sacrificing ease of use. This combination of performance and productivity has fueled Julia‘s rapid adoption in fields like data mining, machine learning, economics, chemistry, and physics.
2. Rust
Rust is a systems programming language from Mozilla that runs blazingly fast and prevents crashes, data races, and other errors at compile-time. It achieves memory safety without requiring garbage collection, making it useful for performance-critical applications.
Key features of Rust include:
- Memory safety – Statically checks for memory-related errors like dangling pointers, double frees, data races, etc. This eliminates a huge class of bugs.
- Zero-cost abstractions – Abstractions compile down to efficient machine code with minimal overhead. This enables high-level ergonomics without sacrificing performance.
- Concurrency support – Native concurrency features make it easy to write reliable parallel and asynchronous code.
- Cross-platform – Supports Windows, Linux, macOS, FreeBSD and more. Code can be easily portable across platforms.
Rust is gradually replacing C and C++ in systems programming domains like embedded devices, operating system kernels, browsers, databases and simulation engines where software robustness and speed are critical. With its combination of performance, safety and concurrency support, Rust delivers on its promise of being a safe systems language.
3. Kotlin
Developed by JetBrains and first released in 2016, Kotlin is a general-purpose statically typed language that runs on the Java Virtual Machine (JVM) and can be compiled to JavaScript. It was designed from the ground up to be more concise and safer than Java.
Here are some noteworthy features of Kotlin:
- Interoperability – Fully interoperable with existing Java code and libraries which facilitates migration.
- Safety – Prevents entire classes of errors such as null pointer exceptions.
- Conciseness – Far less boilerplate code compared to Java due to features like type inference, lambdas, etc.
- Tooling – Great IDE support with useful refactoring and code generation features.
Kotlin has already been adopted by major companies like Google, Pinterest and Atlassian. It is now Google‘s preferred language for Android development. With a vibrant ecosystem and robust tooling support, Kotlin is likely here to stay as a pragmatic and productive JVM language.
4. Elixir
Built on top of the battle-tested Erlang VM known for rock-solid reliability and fault tolerance, Elixir is a dynamic functional language that combines Erlang‘s robustness for building distributed, fault-tolerant applications with an approachable Ruby-like syntax.
Key features include:
- Excellent concurrency – Uses Erlang‘s actor model to achieve unrivaled concurrency support.
- Fault tolerance – Builds on top of the Erlang VM‘s mechanisms for resilience to software faults and hardware failures.
- Functional style – First-class functions, pattern matching, immutable data structures and explicit state management.
- Dynamic and extensible – New code can be loaded and evaluated dynamically without stopping your application.
With lightweight processes, asynchronous I/O, fast recovery from failures and effortless distribution across cores and nodes, Elixir makes it remarkably easy to build concurrent applications that scale up elegantly. Companies like Mozilla, Pinterest, WhatsApp, The New York Times and Discord are already leveraging Elixir to build scalable real-time platforms.
5. ReasonML
Developed by Facebook and released in 2016, ReasonML (or just Reason) is an attempt to improve JavaScript by offering a safer and simpler syntax and type system while compiling seamlessly to JavaScript.
Here are some key aspects of Reason:
- Sound type system – Provides compile-time type safety which eliminates large classes of runtime errors.
- Familiar syntax – Syntax and keywords are similar to languages like JavaScript with a few modifications to enable type safety.
- Strict semantics – Fixes confusing or unintuitive behaviors in JS like implicit globals, scope ambiguity, etc.
- JavaScript Interoperability – Compiles to readable JavaScript that can integrate with existing JS codebases.
By providing soundness, safety and simplicity on top of JavaScript runtimes, Reason empowers JS developers to write complex web applications with more confidence. Many major JS projects and frameworks already have Reason bindings available. With Facebook heavily investing in it, Reason seems poised to drive the future of front-end development.
6. Crystal
Crystal is a compiled, statically-typed language with ruby-inspired syntax that aims for C-like performance along with type safety and memory safety guarantees. It runs on all major operating systems.
Here are some notable aspects of Crystal:
- Ruby-like syntax – Reads almost like Ruby but with a focus on type safety. Easy integration for Ruby developers.
- Statically typed – Type safety enables earlier detection of bugs during compilation.
- Fast execution – Compiles to optimized native code using LLVM. Benchmarking puts it quite close to C and C++ in performance.
- Concurrency support – Lightweight processes make it easy to leverage multi-core parallelism.
- Memory safety – Built-in memory management prevents issues like buffer overruns.
With its unique combination of high performance, type safety and ruby-like expressiveness, Crystal fills an important niche for infrastructure components, system tools, servers and low-latency applications. It is already being used by companies like Siemens, Volkswagen and Amazon Web Services.
7. Pony
Pony is an open-source, object-oriented programming language designed for concurrent and distributed applications that require high reliability and performance. Notable aspects of Pony include:
- Actor-based concurrency – The language uses actors with isolated mutable state as a concurrency abstraction which prevents data races and deadlocks.
- Capability-based security – Pony utilizes object capabilities to achieve memory safety and improve security. References can‘t be forged.
- Performance – Leverages compiler technology to generate highly optimized machine code.
- Mathematical soundness – Formal proofs establish properties like type safety, memory safety, no data races, deadlock freedom etc.
With mathematical soundness guarantees, high developer productivity through built-in concurrency, safety and an intuitive object model, Pony enables constructing robust distributed systems at scale. Its niche in mission-critical computing is reflected in use cases like financial trading platforms, control systems and sensor networks.
8. WebAssembly
WebAssembly (WASM) is a low-level bytecode format for the web that runs with near native performance in modern web browsers. It offers a compilation target for languages besides JavaScript and bridges compatibility gaps between web apps, servers, mobile apps and native desktop apps.
Why WebAssembly matters:
- Native performance – Offloads compute intensive code from JS to native hardware capability, leading to massive speedups.
- Language flexibility – Can use any language like C/C++, Rust that compiles to WASM, not just JS.
- Code portability – Enables reusing existing software libraries and applications on the web by compiling them to WASM bytecode.
- Mobile compatibility – Runs the same WASM code on both desktop and mobile web browsers.
By enabling native hardware acceleration for web apps along with code reuse and portability across environments, WebAssembly promises to greatly expand web capabilities and become the "Assembly language of the web". Its growing support in browsers and fundamental advantages make WASM an essential technology for the future of web development.
9. Vyper
Vyper is a Python-like programming language for writing smart contracts on the Ethereum blockchain platform. It prioritizes simplicity, security and auditability to prevent common vulnerabilities and errors that have led to issues with other blockchain languages.
Why Vyper stands out:
- Human readable syntax – Clean syntax based on Python to support writing transparent, easy to understand smart contracts.
- Security focus – Prevents overflow errors, out of gas exceptions, reentrancy issues that can lock funds indefinitely.
- Formal verification support – Enables mathematical proofs of correctness to ensure code matches specifications and intended behavior.
As blockchains process increasingly complex financial transactions, Vyper‘s emphasis on auditability sets it apart as a language tailored for writing reliable smart contracts that clarify permissions and constraints. With its security and simplicity advantages, Vyper seems poised to gain wider adoption among blockchain developers.
10. Zig
Zig is an open-source system programming language focused on optimization, robustness, and clarity. It compiles to common platforms like Linux, Windows, macOS and BSD to create small, tight binaries.
Notable aspects include:
- Robust build system – Powerful native build system to manage compilation of Zig code across different targets.
- Low-level control – Support for SIMD, multiple memory allocators, cross-calling C code, etc.
- Resource-awareness – Controllable tradeoffs between compile times, binary sizes, tunable optimizations.
- Readability – Clean, consistent syntax focused on transparency and understanding code at a glance.
Zig essentially attempts to build an improved C/C++ without historical design restrictions and with greater focus on modern hardware capabilities like vectorization and parallelism. Its systematic design and high self-consistency makes it beginner friendly while still useful for low-level systems programming.
11. Odin
Odin is an open-source compiled programming language in the tradition of C without its historical baggage and unsafe behaviors. It focuses on simplicity, uniformity and performance.
Key aspects:
- Speed and small output size – Compiles quickly to small, efficient machine code using whole-program optimization techniques.
- Type safety and memory safety – Design emphasizes avoiding crashes, data corruption, leaks etc.
- Easy interoperation with C code – Can import existing C libraries which facilitates reusing system interfaces.
- Intuitive syntax – Clean, regular syntax without irregular special cases to remember.
Odin aims to create a safe systems language that retains C‘s control, speed and small binary sizes while improving reliability and security compared to C. With its intuitive design, Odin makes systems programming more accessible to programmers familiar with scripting languages.
12. Carbon
Carbon is an emerging general-purpose statically typed language influenced by C and Go that focuses on cloud infrastructure software. It provides built-in support for technologies used in modern cloud platforms.
Key features:
- Native concurrency and network programming – Contains primitives for goroutines and channels like Go for concurrent software.
- Cloud runtime support – Supports distributed tracing, structured logging, global rate limiting etc. used in cloud-based services.
- Simplicity and stability – Avoids complex language mechanisms that inhibit reasoning about code behavior.
- Performance – Compiles to efficient machine code with low overhead and small binary sizes via LLVM.
As a language tailored for the cloud, Carbon allows developers to build resilient distributed systems easily without sacrificing reliability or speed. Its design choices reflect the increasing relevance of cloud platforms and aim to close the gap between infrastructure needs and available programming models.
