The State of Benchmarking in Node.js

Published by on (last update: )

Benchmarking becomes more important as we build more and more applications and tooling for runtimes like Node.js and Bun. This article is about macro and micro benchmarking, and explores options we can use today. The article includes code examples and a CodeSandbox to try and implement in your own applications.

Contents

Macro benchmarking

Benchmarking a part of your application code is an important scenario. While running a real-world application, how many times are expensive functions called and how much time is spent in each? These are essential metrics for any CPU intensive code such as bundlers, compilers, linters, formatters, and so on.

Not many of those tools are using the node:perf_hooks module, while much of this native module is available since Node.js v8.5.0 (released over 6 years ago). This included performance.now(), performance.timerify() and PerformanceObserver, and the built-in module has been improved and extended ever since. This module allows to integrate all sorts of performance timings right into your application.

Ecosystem

There aren’t that many libraries or runners on top of the Node.js built-ins. I sure hope I’m missing something, but here are some data points at the time of writing:

I think there’s room for tooling in this space to reduce boilerplate and improve accessibility. For instance, it would help a lot if we could import a utility to wrap functions in any application, and render or return metrics about the wrapped functions as needed.

Example: PerformanceObserver for functions

Let’s look at an example which logs each recorded function invocation with a PerformanceObserver instance:

const fnObserver = new PerformanceObserver(items => {
items.getEntries().forEach(entry => {
console.log(entry);
});
fnObserver.disconnect();
});
fnObserver.observe({ entryTypes: ['function'] });
function myFunctionUnderTest() {
// Such intensive, very cpu, much wow
}
const wrapped = performance.timerify(myFunctionUnderTest);
wrapped();
wrapped();
wrapped();

This will log three PerformanceEntry objects and one of the properties is duration:

$ node observer.mjs
PerformanceNodeEntry {
name: 'myFunctionUnderTest',
entryType: 'function',
startTime: 20.211291000247,
duration: 0.02987500000745058,
detail: []
}
PerformanceNodeEntry {
name: 'myFunctionUnderTest',
entryType: 'function',
startTime: 20.426791000179946,
duration: 0.0017919996753335,
detail: []
}
PerformanceNodeEntry {
name: 'myFunctionUnderTest',
entryType: 'function',
startTime: 20.432208000682294,
duration: 0.0006669992581009865,
detail: []
}

Now we have a basis to record the number of calls to a function and the duration of each call.

Note: this article focuses on the function performance entry type. Other valid entryTypes include mark, measure, http, net and dns. See the Node.js docs on perf_hooks for more details and examples.

Example: timerify application code

Expanding on this idea, I was hoping there would be utilities to make this easier and more accessible, but unfortunately I didn’t find much.

Since Node.js provides the building blocks, I created this Performance.js class in Knip last year. I’ve been meaning to turn this into a separate module to be published, but haven’t got around doing this.

For this article I created a modified version to try and play with. The code is in this CodeSandbox.

Run the demo from the terminal inside the sandbox:

node index.js --performance

Here’s the gist of it, again with the PerformanceObserver class and performance.timerify() function as the main building blocks:

import { performance, PerformanceObserver } from 'node:perf_hooks';
import EasyTable from 'easy-table';
import { parseArgs } from 'node:util';
export const timerify = fn => (isEnabled ? performance.timerify(fn) : fn);
export class Performance {
constructor(isEnabled) {
if (isEnabled) {
this.startTime = performance.now();
this.fnObserver = new PerformanceObserver(items => {
items.getEntries().forEach(entry => this.entries.push(entry));
});
this.fnObserver.observe({ entryTypes: ['function'] });
}
}
getTable() {
const entriesByName = this.entries;
const table = new EasyTable();
// ..build table..
return table.toString().trim();
}
getTotalTime() {
return this.endTime - this.startTime;
}
async finalize() {
this.endTime = performance.now();
}
}

And here’s how to use it in any real-world application:

import { setTimeout } from 'node:timers/promises';
const fnA = setTimeout;
const fnB = setTimeout;
const wrap = fn => (isEnabled ? timerify(fn) : fn);
const wrappedA = wrap(fnA); // (1) Wrap functions
const wrappedB = wrap(fnB); // to get metrics when called
async function myApplication() {
await Promise.all([wrappedA(100), wrappedA(200), wrappedA(300)]);
await wrappedB(500);
}
// (2) Installs PerformanceObserver#observe({ entryTypes: ['function'] }) to observe functions
const perfObserver = new Performance(isEnabled);
await myApplication();
await perfObserver.finalize();
console.log(perfObserver.getTable());
console.log('Total running time:', prettyMs(perfObserver.getTotalTime()));
perfObserver.reset();

After running this, here’s some example output:

$ node performance.mjs --performance
Name size min max median sum
---- ---- ------ ------ ------ ------
fnA 3 101.18 300.59 200.70 602.47
fnB 1 502.24 502.24 502.24 502.24
Total running time: 804ms

The functions are only wrapped when using the --performance flag. Without the flag, the functions are not wrapped and there is no overhead.

Micro benchmarking

Benchmarking arbitrary code in isolation is important too. Sometimes you want to benchmark and compare two or more ways to do the same thing. Paste some code, let it ramble for a bit and see results. There’s plenty of options available to do this in a browser, but what about Node.js and other runtimes?

We have options console.time() and performance.now(), but there’s some boilerplate and ceremony involved to get results.

And we shouldn’t have to worry about things like process isolation, state resets between runs, external conditions, turbulence, and aggregating numbers to yield statistically significant results.

For some more serious benchmarking, we’ll need something better.

Ecosystem

Node.js was pretty close to having a built-in node:benchmark module. In November 2023, a pull request to add an experimental node:benchmark module to Node.js core was opened. And closed, after an interesting debate.

This leaves us with a diverse set of packages for micro benchmarking in Node.js:

If you need something production-ready today I would recommend Benchmark.js, because it’s battle-tested and versatile.

For the adventurous, the other options are all worth checking out. Consult the overview table and benchmarks-comparisons that Vinicius Lourenço put together for more details.

For the record, Deno has a built-in benchmark runner.

A CLI for such tools would be great. Have some code in a file and let a CLI tool import and benchmark it. Much like aforementioned tools, but move the API from runtime to CLI.

Pitfalls

Before we continue, here’s the mandatory warning to not forget about the pitfalls of micro benchmarking:

Example: string concatenation

Let’s look at an example. We want to know which function is the fastest, and by how much. The following functions do the same thing:

function join(strings) {
return strings.join('');
}
function concat(strings) {
return ''.concat(...strings);
}

Benchmark.js

Benchmark.js is great and battle-tested software, despite the fact its last publish was early 2017 when it was tested on Node.js version 10 and 11.

Let’s create a test suite to benchmark and compare three string concatenation alternatives:

import Benchmark from 'benchmark';
const strings = ['aa', 'bb', 'cc', 'dd', 'ee', 'ff', 'gg', 'hh'];
function plus(strings) {
let result = '';
for (const str of strings) result += str;
return result;
}
function join(strings) {
return strings.join('');
}
function concat(strings) {
return ''.concat(...strings);
}
const suite = new Benchmark.Suite();
suite
.add('plus', function () {
plus(strings);
})
.add('join', function () {
join(strings);
})
.add('concat', function () {
concat(strings);
})
.on('cycle', function (event) {
console.log(String(event.target));
})
.on('complete', function () {
console.log('Fastest is ' + this.filter('fastest').map('name'));
})
.run();

Running this on my machine gives the following output:

$ node benchmark.mjs
plus x 20,171,223 ops/sec ±0.41% (94 runs sampled)
join x 10,288,969 ops/sec ±0.19% (101 runs sampled)
concat x 17,782,613 ops/sec ±0.18% (98 runs sampled)
Fastest is plus

Clear output. All options are fast, but we have a winner.

Tinybench

Tinybench is the new kid on the block. You can use it stand-alone, and it also comes shipped with Vitest.

The API of Tinybench is similar to Benchmark.js:

import { Bench } from 'tinybench';
const suite = new Bench();
suite
.add('plus', function () {
plus(strings);
})
.add('join', function () {
join(strings);
})
.add('concat', function () {
concat(strings);
});
suite.addEventListener('complete', function () {
console.table(suite.table());
});
suite.run();

Running this gives the following output:

$ node tinybench.mjs
┌─────────┬───────────┬──────────────┬────────────────────┬──────────┬─────────┐
│ (index) │ Task Name │ ops/sec │ Average Time (ns) │ Margin │ Samples │
├─────────┼───────────┼──────────────┼────────────────────┼──────────┼─────────┤
│ 0 │ 'plus' │ '13,188,219' │ 75.8252486995182 │ '±0.61%' │ 6594110 │
│ 1 │ 'join' │ '7,958,935' │ 125.64493939618565 │ '±0.54%' │ 3979468 │
│ 2 │ 'concat' │ '11,681,195' │ 85.60767506752819 │ '±0.91%' │ 5840598 │
└─────────┴───────────┴──────────────┴────────────────────┴──────────┴─────────┘

A CLI, maybe?

Wouldn’t it be convenient if we could just export our functions from a file:

const strings = ['aa', 'bb', 'cc', 'dd', 'ee', 'ff', 'gg', 'hh'];
export function plus(strings) {
let result = '';
for (const str of strings) result += str;
return result;
}
export function join(strings) {
return strings.join('');
}
export function concat(strings) {
return ''.concat(...strings);
}

And point our imaginary bench CLI tool at this file:

$ bench string-concat.js
plus x 20,171,223 ops/sec ±0.41% (94 runs sampled)
join x 10,288,969 ops/sec ±0.19% (101 runs sampled)
concat x 17,782,613 ops/sec ±0.18% (98 runs sampled)
Fastest is plus

And, maybe, one day:

$ node --bench string-concat.js

Conclusion

Although the building blocks are there, I think especially in the area of macro optimizations there’s room for tooling to make our lives easier.

When it comes to micro benchmarking, it feels a bit odd to recommend a package last updated in 2017 (Benchmark.js). Let’s watch this space!

This concludes my perspective on the current state of benchmarking in Node.js, at the end of 2023. Do you agree?