Concurrency In Rust; Can It Stack Up Against Go’s Goroutines?

One of the primary goals of the Go programming language is to make concurrency simpler, faster, and more efficient. With Rust growing in popularity let’s see how its concurrency mechanisms stack up against Go’s.

A Refresher On Goroutines

In Go, concurrency is accomplished by spawning new goroutines:

package main

import (

func main() {
	go func() {
		for {
			fmt.Println("one second passed")
	fmt.Println("waiting 10 secs for goroutine")
	time.Sleep(time.Second * 10)

In the example above, we use the go keyword to signify that we want to run the provided anonymous function in a goroutine. Execution at that point splits – execution continues on the main thread, but the runtime is now running the goroutine in parallel.

Goroutines are lightweight and take advantage of all of the processing power available. If two goroutines are running they will efficiently use at most two cores. If one hundred goroutines are running they will use at most one hundred cores, but can efficiently run on as few as one.

What About Rust?

In Rust, there are two approaches we can take to run code concurrently. Async/Await, and threading. Async/Await is a paradigm that is orthogonal to threading, which means that it has the potential to run tasks on a single thread OR on multiple threads depending on the executor that is used.

Threading on its own makes use of multiple cores and uses typical operating-system threads.


Let’s take a look at async first. and don’t forget to add the following dependencies to your project’s Cargo.toml:

futures = "0.3.5"
async-std = "1.5.0"
use std::time::Duration;
use futures::executor::block_on;
use async_std::task;

fn main() {
    let future = async_main();

async fn async_main() {
    print_for_five("await 1").await;

    let async_one = print_for_five("async 1");
    let async_two = print_for_five("async 2");

    futures::join!(async_one, async_two);

async fn print_for_five(msg: &str) {
    for _ in 0..5 {
        println!("one second has passed: {}", msg)

We start by creating a new async function, async_main, then use the block_on executor to block and execute async_main. Because async_main is an asynchronous function, we are able to await other async functions inside of it, as well as execute them concurrently.

The first call in async_main is an await on our async print_for_five function which prints the message “one second has passed: await 1” once each second for 5 seconds. Because we used the await keyword, async_main will block and wait for print_for_five.

Next, we create two futures (very similar to JavaScript promises) by calling print_for_five anew with new messages. The futures do not begin execution until the next line where we use the join macro. Join executes the futures concurrently and blocks until all the futures have completed. Join is very similar to JavaScript’s PromiseAll.

The program will print the following:

one second has passed: await 1
one second has passed: await 1
one second has passed: await 1
one second has passed: await 1
one second has passed: await 1
one second has passed: async 1
one second has passed: async 2
one second has passed: async 1
one second has passed: async 2
one second has passed: async 1
one second has passed: async 2
one second has passed: async 1
one second has passed: async 2
one second has passed: async 1
one second has passed: async 2

Where the last ten lines are all printed within five seconds of each other because print_for_five("async 1") and print_for_five("async 2") were executed concurrently.

The block_on executor that we used blocks the main thread, which means that all the concurrency happened on a single thread.

Rust’s Threading

Threading in Rust takes advantage of multi-core hardware. When a new thread is spawned, the operating system knows that these separate threads of the program can be executed in parallel on different cores at exactly the same time.

Let’s take a look at the following example:

use std::thread;
use std::time::Duration;

fn main() {
    thread::spawn(|| {
        for _ in 1..10 {
            println!("Hello after 1 second from the spawned thread");

    for _ in 1..5 {
        println!("Hello after 1 second from the main thread");

We spawn a new thread using the standard library’s spawn function. The spawn function take a closure as its argument and executes it in parallel. As you can see by running the program, it only takes five seconds to print all ten statements because each thread is sleeping independently.

Which is Best?

You’ve heard it before but no approach is best, they are all just different. I argue that Go is the best at keeping it simple. Go provides only one method (goroutines) to achieve concurrency, and the syntax is elegant. Rust provides two methods which are tailored to different problems.

Goroutines vs Async/Await

Goroutines are very different from async/await. Async/Await explicitly accomplishes concurrency, but not necessarily parallelism. In other words, while async/await logically executes two functions at once, it doesn’t always practically do so. It all depends on the executor that is used.


Async/Await is a useful paradigm for programs that have heavy I/O wait times but aren’t doing long-running compute-heavy workloads.

Async/Await can also be good for many short-lived async tasks where new operating system threads would be clunky and expensive.

Goroutines vs Threading

Goroutines are more lightweight and efficient than operating-system threads. As a result, a program can spawn more total goroutines than threads. Goroutines also start and clean themselves up faster than threads due to less system overhead.

The big advantage of traditional threading (like that of Rust) over the goroutine model is that no runtime is required. Each Go executable is compiled with a small runtime which manages goroutines, while Rust avoids that extra fluff in the binary.

Thanks For Reading!

Take computer science courses on our new platform

Follow and hit us up on Twitter @q_vault if you have any questions or comments

Subscribe to our Newsletter for more programming articles

Related Reading

%d bloggers like this: