Concurrency might sound like a technical term, but it boils down to a program performing multiple tasks at once, as if it’s multitasking. Imagine you’re cooking: while the pasta is on the stove, you start the washing machine and charge your phone. Although you’re not doing everything at the exact same moment, it all happens smoothly side by side. Software that supports concurrency works the same way: a program can, for instance, download files, perform calculations, and send data to a server all at once. This multitasking makes the use of computing power more efficient and ensures faster, smoother performance.

Golang / Go excels at making concurrency simple and intuitive. Using so-called goroutines, Go offers a lightweight and efficient solution for multitasking, unlike traditional threads in, say, Java. Java threads often consume significant amounts of memory (typically megabytes per thread), whereas goroutines are much lighter and demand fewer system resources. This makes Go particularly well-suited for modern applications like microservices, where scalability plays a key role.

Classic mistakes are avoided

With Go, common multitasking issues are effectively sidestepped. This makes it more reliable than traditional solutions. It helps you avoid classic errors such as:

  • Race conditions: Issues caused by simultaneous data access.
  • Deadlocks: Situations where processes block each other.
  • Resource leaks: Inefficient use of system resources.

These advantages make Go not only powerful but also a stable choice for companies looking to develop efficient, error-free software.

Real-time systems and alternatives

While Go is exceptional in its simplicity and strength, it’s less suited for real-time systems. That’s because Go has a garbage collector, a feature that automatically frees up unused memory space. While this is handy for most applications, it can occur at unexpected moments and cause delays. The same applies to Java, which also relies on garbage collection. For real-time systems, where every millisecond counts, languages like C, C++, and Rust are better options. These languages provide direct control over memory management and are designed with performance and predictability in mind.

An interesting approach is to combine the best of both worlds. For real-time requirements, you can write modules in C, C++, or Rust and integrate them with Go, for example. This way, you benefit from Go’s simplicity and scalability while leveraging the reliability and speed of languages like C or Rust.

Go offers a modern, efficient solution for concurrent software and helps prevent classic mistakes. For situations where real-time performance is critical, languages like C or Rust provide a robust foundation. With the right combinations, you can tackle almost any challenge! Feel free to reach out if you’d like to know more or need advice. 😊

P.S.
The information I’ve found here sparks my imagination and has made me curious to dig deeper and see what I can prove myself. However, in an attempt to demonstrate and compare actual memory statistics, some things aren’t as straightforward as they seem. The memory usage of goroutines heavily depends on how much memory is allocated through them rather than having a clear initial memory footprint. So, I’m testing the information I’ve found and the claims made within it.