jackyef / ssr-benchmarks

Simple benchmark of various SSR approaches, rendering 64k divs in a recursive way

ssr-benchmarks

Want to see the results? Go straight to result.md

Benchmarks of various approaches to SSR:

• ✅ react-ssr (using react-dom)
• ✅ preact-ssr (using preact-render-to-string)
• ✅ react-htm-ssr (using react-dom after transforming JSX to htm tagged template literals)
• ✅ preact-htm-ssr (using preact-render-to-string after transforming JSX to htm tagged template literals)
• ✅ react-esx-ssr (using esx)
• ✅ lithtml-ssr (using @popeindustries/lit-html-server)
• ✅ svelte-ssr
• ⚠️ vue-ssr (the numbers seem very out-of-place, I might have implemented it wrongly. If you know about vue, please consider helping by taking a look at methods/vue-ssr implementation)
• ✅ vhtml
• ✅ vhtml-htm
• ✅ vanilla-function (plain old javascript function)
• ⚠️ ejs (the numbers are worse than React, either EJS has problems rendering recursive includes, or I did something wrong. If you know about ejs, please consider helping by taking a look at methods/ejs implementation)
• ⚠️ solid-ssr (the numbers seems off, they should be faster than React. If you know what I am doing wrong, please consider helping by taking a look at methods/solid-ssr implementation)
• Give me your ideas on what we should include in this benchmark! You can contribute directly, or just open an issue and name the approach you want to benchmark.

Setup

This project uses pnpm. If you do not have pnpm yet, install it globally.

# npm
npm install -g pnpm

# yarn (v1)
yarn global add pnpm

Then just install the dependencies using pnpm

pnpm install

Running the benchmarks

pnpm run build:all
pnpm run bench:all

Result is outputted to result.md

Running specific benchmark

pnpm run bench --filter <method-name>

Example:

pnpm run bench --filter react-ssr

The benchmark

The benchmark tests various approaches to see how long it takes for each to render around 64000 <div>s on the server side. Basically it goes like this:

1. We warm up the v8 engine by rendering 20 times
2. We then run the actual benchmark by rendering 30 times
3. We collect the average time and the standard deviation

Do note that the results are based on runs on my machine.