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Egg vs Fastify

Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.

Egg

Open source · MIT

A Node.js framework built on Koa for building larger server-side apps, with plugins and process management.

Fastify

Open source · MIT

A fast, low-overhead web framework for building servers and APIs with Node.js.

The short answer

Choose Egg if you need…

  • Teams building larger Node.js backend applications that need structure
  • Developers who already know Koa and want a more opinionated layer on top
  • Projects that want to use a plugin ecosystem (the README links to plugins tagged egg-plugin)
  • TypeScript developers, since the project is written in TypeScript and includes a TypeScript example

Choose Fastify if you need…

  • Node.js developers building JSON APIs or backend services
  • Teams that care about request throughput and want a lightweight framework
  • Projects that want schema-based validation of routes and responses
  • Developers who want to organize code into reusable plugins

Side-by-side

EggFastify
TypeFrameworkLibrary
PriceFree and open sourceFree and open source
LicenceMITMIT
GitHub stars19k37.3k
Setup difficultyIntermediateBeginner
How you get itInstall with a package managerInstall with a package manager
Main languageTypeScriptJavaScript
Last code update14 days ago4 days ago

What each one is

Egg

Egg is a Node.js framework built on top of Koa, aimed at larger web applications and enterprise-style backends. According to its README, it provides built-in process management, a plugin system, and the ability to customize the framework itself. The README describes it as a monorepo with a main framework package, example apps, and a documentation site.

Fastify

Fastify is a framework for building web servers and APIs in Node.js. You define routes, such as a URL that returns data, and Fastify handles incoming requests with minimal extra work per request. It also offers a plugin system, input and output validation using JSON Schema, and built-in logging through Pino.

Best for

Egg

  • Teams building larger Node.js backend applications that need structure
  • Developers who already know Koa and want a more opinionated layer on top
  • Projects that want to use a plugin ecosystem (the README links to plugins tagged egg-plugin)
  • TypeScript developers, since the project is written in TypeScript and includes a TypeScript example

Fastify

  • Node.js developers building JSON APIs or backend services
  • Teams that care about request throughput and want a lightweight framework
  • Projects that want schema-based validation of routes and responses
  • Developers who want to organize code into reusable plugins

Strengths

Egg

  • Large existing ownership signals: about 19,000 GitHub stars and an MIT license, per the metadata
  • Built-in process management and a plugin system are listed as core features
  • Documentation site and plugin search links are provided in the README

Fastify

  • The README reports high request throughput in a synthetic hello-world benchmark, with the caveat that real results depend on the application
  • Supports JSON Schema validation and serialization for routes
  • Includes a plugin architecture and hooks for extending behavior

Not ideal for

Egg

  • Beginners looking for a very small, minimal server library: the README lists many features and a monorepo setup, which adds learning overhead
  • Projects that cannot run Node.js 22.18.0 or newer, which the README lists as required
  • Teams not comfortable with the utoo tooling shown in the quickstart, since the README uses it rather than plain npm commands

Fastify

  • Beginners who have not yet learned Node.js basics, since the framework assumes JavaScript familiarity
  • Projects that need a non-Node.js language, because Fastify is for Node.js only
  • Teams expecting a large built-in feature set; much functionality comes from plugins, per the docs

Trade-offs

Egg

  • The quickstart relies on the utoo tool (ut commands) rather than the more common npm workflow, which may be unfamiliar
  • Some tests need local MySQL and Redis via Docker, and the README notes specific hard-coded ports for those services
  • The README is truncated in our source, so details beyond the quickstart and dev notes are not verified here

Fastify

  • Benchmark figures come from the maintainers' own synthetic test and may not match your workload
  • The README's benchmark table lists an older Fastify version (4.0.0), so the numbers are not current
  • Binding to 0.0.0.0 in containers requires care, since the README warns of security risks

Getting started

Egg

Install utoo globally

npm install --global utoo@latest

Create a project directory

mkdir showcase && cd showcase
Step-by-step guide: how to use Egg

Fastify

Install Fastify in an existing project

npm i fastify

Generate a new Fastify project

npm init fastify
Step-by-step guide: how to use Fastify

Frequently asked questions

What is the difference between Egg and Fastify?

Egg: A Node.js framework built on Koa for building larger server-side apps, with plugins and process management. Fastify: A fast, low-overhead web framework for building servers and APIs with Node.js. Egg suits teams building larger node.js backend applications that need structure, while Fastify suits node.js developers building json apis or backend services.

Are Egg and Fastify free?

Egg: Free and open source. Fastify: Free and open source.

Which is easier to set up, Egg or Fastify?

Fastify is easier to get started with (rated beginner); Egg is rated intermediate and usually needs more setup.

Is Egg or Fastify more popular?

Fastify has more GitHub stars (37.3k) than Egg (19k). Popularity isn't the same as fit — check which one matches your use case above.

What are other alternatives to Egg and Fastify?

Other options people compare them with include Koa, Express, LangChain, Ant Design Pro.

Keep comparing

Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.