Comparing Documentation Site Generators — Hugo, MkDocs, Docusaurus, Starlight: Which One to Pick

Once you’ve decided to build your team docs as a static site, the next question is fixed: which tool do you build it with? There are many candidates, but in practice four come up again and again. This post is here to help you choose, based on actually building all four (Hugo, MkDocs, Docusaurus, Starlight) end to end.

The four candidates #

  • Hugo — A static site generator written in Go. Hextra is the go-to docs theme. A single binary and overwhelming build speed are its strengths.
  • MkDocs — Python-based. Paired with the Material theme, it stays minimal and tidy in configuration.
  • Docusaurus — React-based. The heaviest but highest-ceiling tool, with MDX and first-class i18n and versioning.
  • Starlight — A docs theme built on Astro. A relatively recent option, great for putting a marketing site and docs in one project.

At a glance #

ToolRuntimeInstallSearchVersioningi18nCeiling
Hugo (Hextra)Go single binaryMedium (needs Go)Built-inNone (manual folders)Built-inTheme-bound
MkDocs (Material)PythonEasy (pip)Built-inmike (plugin)PluginTheme + extensions
DocusaurusNode / ReactHeavySeparate (Algolia / plugin)Built-inBuilt-inHighest (MDX / React)
StarlightNode / AstroMediumBuilt-in (Pagefind)PluginBuilt-inAstro components

Runtime is the entry barrier #

The first thing that splits the tools is which language they run on. Hugo is a single binary so it installs lightly, but a module theme like Hextra needs Go. MkDocs is one pip install line, the most natural fit for a Python team. Docusaurus and Starlight run on the Node ecosystem. In the end, the side that matches the language your team already uses causes the fewest surprises.

Who gives you search for free #

In a manual, search is not optional but essential. This is where only Docusaurus differs. Hugo Hextra, MkDocs Material, and Starlight ship search built in and work without a server, but Docusaurus requires you to wire up Algolia DocSearch or a local search plugin yourself. If you want search up fast, the other three are a step ahead.

When you need versioning #

If your product version goes up often and you have to keep old docs around, this axis is decisive. Docusaurus has versioned snapshots and a version dropdown built in. MkDocs adds something similar with a tool called mike, and Starlight with a community plugin. Hugo has no dedicated feature, so you split versions into folders by hand. The stronger your versioning needs, the more Docusaurus wins.

Ceiling — how far can you customize #

If you need interactive elements or custom pages beyond plain docs, the ceiling matters. Docusaurus has the highest ceiling with MDX, which lets you use React components inside Markdown. Starlight offers similar flexibility with Astro components. Hugo and MkDocs are the kind that work cleanly within the range their theme and extensions define.

Starting in one line #

Here is the command to create a first site with each tool.

Create a first site — by tool
# Hugo + Hextra
hugo new site my-docs && cd my-docs && hugo mod get github.com/imfing/hextra

# MkDocs Material
pip install mkdocs-material && mkdocs new .

# Docusaurus
npx create-docusaurus@latest my-docs classic

# Starlight
npm create astro@latest -- --template starlight

Recommendations by situation #

  • Lightest and fastest, done with a single binaryHugo
  • A Python team that wants minimal configuration kept tidy → MkDocs Material
  • Large product docs with lots of versions and languages, and you want to use React → Docusaurus
  • Adding docs onto a marketing site, or using the Astro ecosystem → Starlight

There is no single right answer. Weigh three factors — the language your team already uses, how strong your search and versioning needs are, and how high your customization ceiling needs to be — and it naturally narrows to one tool.

Going deeper — hands-on series per tool #

The full process of building a docs site with each tool, from install through deploy and operations, is written up as a series.

All four series follow the same six-part outline (install → information structure → content → deploy → i18n and versioning → operations), so they read well side by side too.

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