2x faster than Encore - 1 year later

On Jun 17 2024, Encore published a blog post, 9x faster than Express.js, 3x faster than ElysiaJS & Hono claiming that Encore was faster than Elysia & Hono by 3x.

Today, after 1.5 years of development, Elysia is now 2x faster than Encore in the same benchmark.

EncoreTS is a framework powered by a multi-threaded Rust runtime with bindings for Node.js. It leverages Rust’s performance and safety features to build high-performance web applications.

Encore claims to be faster than Elysia & Hono by utilizing Rust for performance-critical tasks, while still providing a familiar JavaScript/TypeScript interface for developers.

Benchmark on EncoreTS homepage

1.5 years later, we revisited the benchmark to see how Elysia performs against Encore.

The benchmark is publicly available on Encore’s GitHub. We forked the repository to run the benchmark with the latest version of Elysia.

After some inspection, we noticed that the original benchmark for Elysia was not optimized for production. We made the following changes to ensure a fair comparison.

Here are some of the changes we made:

1. Add bun compile to Elysia script to optimize for production
2. Update Elysia bare request to use static resources
3. Due to machine specifications, we updated oha concurrency from 150 to 450 to scale the upper limit

Lastly, we updated all the necessary dependencies to their latest versions.

• Encore: 1.5.17
• Rust: 1.91.1
• Elysia: 1.4.16
• Bun: 1.3.2

Here’s the machine specification we used for the benchmark:

• Benchmark Date: 14 Nov 2025
• Machine specification: Intel i7-13700K, DDR5 32GB 5600MHz
• OS: Debian 11 (bullseye) on WSL - 5.15.167.4-microsoft-standard-WSL2

After running the benchmark, we obtained the following results.

Benchmark result: Elysia is 2x faster than Encore

Using the original benchmark, Elysia outperforms Encore in all categories, achieving double the requests per second in all tests.

Here’s a video-proof step-by-step on how to run the benchmark.

In the original benchmark, the Elysia version was 1.1.16. Since then, we have made significant improvements to Elysia’s performance through various optimizations and enhancements.

But to summarize, in a single year, both Elysia and Bun have made significant performance improvements.

In the original Encore benchmark, Elysia performs data normalization on every request, which adds significant overhead to the request processing time.

The bottleneck is not in data validation itself, but due to the normalization process that involves dynamic data mutation.

In Elysia 1.3, we introduce Exact Mirror to accelerate data normalization using JIT compilation instead of dynamic data mutation.

This improves the performance of data normalization significantly, up to ~30x faster for medium size payloads.

Exact Mirror run on medium size payload resulting in 30x faster

This significantly improves validation performance in Elysia.

Between Elysia 1.1 (upstream) and 1.4 (current), we have made several JIT optimizations to improve the overall performance of Elysia especially with Sucrose, our JIT compiler for Elysia.

These optimizations include:

• Constant folding, inlining lifecycle events
• Reducing validation, and coercion overhead
• Minimizing the overhead of middleware and plugins
• Improving the efficiency of internal data structures
• Reducing memory allocations during request processing
• Various other micro-optimizations

In Bun 1.2.3, Bun also offers a built-in routing in native code for better performance.

In Elysia 1.3, we leverage Bun’s native routing when possible to improve routing performance.

In the original benchmark, Elysia was not compiled for production.

Using bun compile optimizes the Elysia application for production, resulting in significant performance improvements, and reduced memory usage.

Through constant improvement, Elysia has optimized its performance significantly over the past 1.5 years, resulting in a framework that is now 2x faster than Encore in the same benchmark.

Benchmarks are not the only factor to consider when choosing a framework. Developer experience, ecosystem, and community support are also important factors to consider.

We have detailed our steps on how to run the benchmark, and recommend you run the benchmark on your own machine for the most accurate results for your use case.