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SSR Framework Benchmark

What is the project about?

This project is a benchmark comparing the server-side rendering (SSR) performance of various JavaScript frameworks and renderers. It was initiated in response to a claim that Next.js is significantly slower in SSR compared to vanilla React.

What problem does it solve?

The project aims to provide a comparative analysis of SSR performance among different frameworks, helping developers understand the relative speed and efficiency of each. It addresses the lack of readily available, direct comparisons beyond simple "hello world" examples.

What are the features of the project?

  • Comparative Benchmarking: Measures operations per second (ops/sec), average rendering time, and response body size for various frameworks.
  • Data Duplication Analysis: Indicates the data duplication factor, crucial for understanding hydration overhead.
  • Realistic Scenario: Uses a more complex rendering scenario (a table with 1000 rows and two UUID columns per row) than a basic "hello world" test.
  • Async Data Handling: Emulates asynchronous data loading and uses Suspense (where applicable) to reflect real-world application behavior.
  • Streaming Rendering: Leverages streaming rendering where supported (Solid, React, Vue) for a more accurate performance assessment.
  • Controlled Environment: Minimizes external factors by mocking HTTP requests/responses and disabling caching mechanisms (like Next.js's route cache) to isolate SSR performance.

What are the technologies used in the project?

  • Frameworks: Next.js (both App Router and Pages Router), React, SvelteKit, Remix, Nuxt, Qwik City, Astro, MFNG (a minimal React Server Components implementation).
  • Renderers: Marko, Kita, Hono, Vue, React, Qwik, Solid.
  • Runtime: Node.js (v20.6.1).
  • Build/Run Tools: npm.

What are the benefits of the project?

  • Performance Insights: Provides quantifiable data on the SSR performance of popular frameworks.
  • Informed Decisions: Helps developers choose the right framework based on their SSR performance needs.
  • Hydration Awareness: Highlights the impact of hydration on response size and performance.
  • Open Source: Allows for community contributions and further analysis.

What are the use cases of the project?

  • Framework Selection: Developers can use the benchmark results to guide their choice of framework for projects where SSR performance is critical.
  • Performance Optimization: The benchmark can be used as a starting point for identifying performance bottlenecks in existing applications.
  • Framework Development: Framework authors can use the benchmark to identify areas for improvement in their SSR implementations.
  • Research and Analysis: The project provides a basis for further research into SSR performance and optimization techniques.
ssr-benchmark screenshot