21 karma · joined August 18, 2025
Do refer the READ me for further information.
Also regarding the performance its written using Rust and raw Hyper library unlike deno runtime no overhead coz I just build a complex rust native addon for node js that allows every one to harness the true power of Rust's Tokio and hyper.
Regarding hono it's my fav and edge based. The Framework I created allows you to run true multi thread Fullstack app on a instance like running raw c++ or golang frameworks. My framework gives you true parallelism without Node.js cluster. Just give a try.
Need suggestions and improvements for this project https://www.npmjs.com/package/brahma-firelight
I gave it my best and eventually published this framework on npm. Many people asked for async support, and after countless sleepless nights, I finally achieved it. Meet Brahma-JS (brahma-firelight) one of my finest creations that replaces Node.js tcp / http module with Rust's Tokio and Hyper library inspired from Deno runtime.
``` Running 10s test @ [http://127.0.0.1:2000/hi](http://127.0.0.1:2000/hi) 1 threads and 200 connections Thread Stats Avg Stdev Max +/- Stdev Latency 1.51ms 479.16us 7.89ms 78.17% Req/Sec 131.57k 9.13k 146.78k 79.00% 1309338 requests in 10.00s, 186.05MB read Requests/sec: 130899.58 Transfer/sec: 18.60MB
``` Oh sure, just another framework casually doing 130k+ requests/sec. No big deal. Totally normal. Definitely not powered by a Rust beast disguised as friendly JavaScript.
Now I have released v1.5 A stable release with support for Mac, Linux and Windows too. You can give a try by starting
``` npm i brahma-firelight
```
Parsing with this WASM build: ~16ms (on Chrome, M1 Mac).
Parsing with JS (SheetJS): seconds, often >5s, with UI stutter. So the speed difference is very noticeable on big files.
Curious if anyone here has even larger datasets to try!
Loading the whole 100 MB file into memory Blocking the main thread Tabs freezing, fans spinning xlsx-lite does it differently:
Streams ZIP entries (no inflate-to-Vec) Async + cooperative yielding — browser paints while parsing Batch-based parsing (rows in chunks) Memory stays flat, UI stays responsive
npm i brahma-firelight
The idea is to give developers a way to get Rust's speed and memory safety without having to rewrite their application logic. It's a plug-and-play engine that works across Node, Deno, and Bun.
All the heavy lifting—like parsing request bodies and headers—happens in Rust. The benchmarks are promising: on a tiny AWS t2.micro instance, I hit 33.2k requests per second during a load test.
I haven't shared the full codebase yet but will soon. You can find the repo here: