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Top 23 Performance Open-Source Projects
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Gin
Gin is a high-performance HTTP web framework written in Go. It provides a Martini-like API but with significantly better performance—up to 40 times faster—thanks to httprouter. Gin is designed for building REST APIs, web applications, and microservices.
Project mention: Go vs Rust: the only backend language debate that actually matters in 2026 | dev.to | 2026-05-14The broader ecosystem is settled too. Gin and Chi for HTTP routing, sqlc for type-safe queries, Wire for dependency injection if that’s your thing. The compiler errors are readable. Onboarding a new engineer onto a Go codebase takes days, not weeks.
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pretext
15KB zero-dependency TypeScript library for fast, accurate text measurement & layout — 500x faster than DOM methods
AI is assisting you. It'll write efficient code if you guide it to write efficient code. You're not a hapless victim of ai written code.
To give you a concrete examples. Recently pretext library made waves. I looked at the code and noticed that isCJK could possibly faster.
So I spent 30 minutes TELLING claude to write a benchmark and implement several different, hopefully faster, versions. Some claude came up with by itself and some were based on my guidance.
You can see the result here: https://github.com/chenglou/pretext/issues/2
The original isCJK, also written by AI (I assume), was fast. It wasn't obviously slow like lots of human JavaScript code I see.
Claude did implement a faster version.
Could I do the same thing (write multiple implementations and benchmark them) without Claude? Yes.
Would I do it? Probably not. It would take significantly longer than 30 min. and I don't have that much time to spend on isCJK.
Would I achieve as good result? Probably no. The big win came from replacing for .. of with regular for loop. Something that didn't occur to me but Claude did it because I instructed it to "come up with ideas to speed it up". I'm an expert in writing fast code but I don't know everything and I all good ideas. AI knows everything, you just need to poke it the right way.
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Project mention: Fiber – An Express-inspired web framework written in Go | news.ycombinator.com | 2026-02-06
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Project mention: This Month in Solid: v2.0.0 Beta - <Suspense> is Over and Start v2 on the horizon 😎 | dev.to | 2026-04-09
Check the release notes: v2.0.0 Beta - The is Over
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sharp
High performance Node.js image processing, the fastest module to resize JPEG, PNG, WebP, AVIF and TIFF images. Uses the libvips library.
Some packages need to build native dependencies. sharp for example needs to build libvips on the system [0] to work
0: https://github.com/lovell/sharp/blob/main/install/build.js
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No-code database marketing pages will always claim "enterprise-scale performance" but rarely disclose their p99 latency under concurrent load. In our 2024 benchmark of 7 top tools, we found that 4 of them had p99 write latencies 3x higher than advertised when tested with more than 20 concurrent writes per second. For example, Airtable’s marketing claims "unlimited scale" but our benchmark (code example 1) showed a hard cap of 50 concurrent writes per second with 320ms p99 latency—far below the 100ms threshold most user-facing apps require for acceptable checkout or form submission experiences. Always run a 10-minute load test with 2x your expected peak concurrent writes before signing an annual contract. Use the benchmark scripts provided earlier in this article, or open-source tools like k6 (https://github.com/grafana/k6) to simulate realistic traffic patterns. We’ve seen startups lock into 1-year contracts with tools that can’t handle their Black Friday traffic, resulting in $50k+ in lost revenue and emergency migrations. A 2-hour benchmark upfront costs nothing compared to that risk.
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The key to successful caching is understanding your application’s bottlenecks and choosing the right caching strategy for each use case. So before doing any caching or performance improvement, track the bottlenecks using tools like django debug toolbar, django silk. You can also use locust for performance/load testing.
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React Virtualized, React Window (a light-weight alternative with smaller bundle size and simpler API), and React-Window-infinite-loader are node packages for implementing List Windowing in various contexts.
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Project mention: Floating-Point Printing and Parsing Can Be Simple and Fast | news.ycombinator.com | 2026-01-20
It is possible to compress the table using the technique from Dragonbox (https://github.com/fmtlib/fmt/blob/8b8fccdad40decf68687ec038...) at the cost of some perf. It's on my TODO list for zmij.
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gofr
An opinionated GoLang framework for accelerated microservice development. Built in support for databases and observability.
[1] gofr-dev/gofr. (n.d.). gofr: An opinionated GoLang framework for accelerated microservice development. Built in support for databases and observability. GitHub. Retrieved from https://github.com/gofr-dev/gofr
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Atlas
🚀 An open and lightweight modification to Windows, designed to optimize performance, privacy and usability.
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lazysizes
High performance and SEO friendly lazy loader for images (responsive and normal), iframes and more, that detects any visibility changes triggered through user interaction, CSS or JavaScript without configuration.
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Front-End-Performance-Checklist
🎮 The only Front-End Performance Checklist that runs faster than the others
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Project mention: React Won by Default – and It's Killing Front End Innovation | news.ycombinator.com | 2025-09-15
How is inferno? Is it ready for production? I'm not a frontend dev, but been looking for a light weight, fast framework. Inferno looked pretty good alternative to react.
https://github.com/infernojs/inferno
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Project mention: NASA Built Artemis II's Fault-Tolerant Computer | news.ycombinator.com | 2026-04-10
>what is my point? well, i think a web stack ran under an RTOS (and sized appropriately) might be a much more pleasurable experience. Get rid of all those lags, and intermittent hangs and calls for more GB of memory.
... it's not the OS that's source of majority of lag
Click around in this demo https://tracy.nereid.pl/
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Nuitka
Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4-3.13. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
Project mention: Lisp-stat: Lisp environment for statistical computing | news.ycombinator.com | 2025-06-15In my view, the biggest advantages of ahead-of-time compilation is lower binary size, higher performance, and binary portability (in a sense of being able to copy the binary and run it on another system with same architecture and OS, not in the usual sense of being easy to run to a different system architecture or OS).
It is somewhat unknown that Python itself can be compiled, using Nuitka [0] compiler. It still runs Python code, so the performance increase is not as extreme as one would get from rewriting in a fully statically typed code, but the AOT compiled C code is still faster than the interpreter.
[0] https://nuitka.net/
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systeminformer
A free, powerful, multi-purpose tool that helps you monitor system resources, debug software and detect malware. Brought to you by Winsider Seminars & Solutions, Inc. @ https://windows-internals.com
Project mention: Show HN: Network Monitor – a GUI to spot anomalous connections on your Linux | news.ycombinator.com | 2025-11-24I wish Linux had two more things:
- https://github.com/winsiderss/systeminformer power-user process explorer
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NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Performance discussion
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Memory management in C# - Part 2: hands-on
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Why your React Three Fiber gallery drops to 5 FPS and how to fix it
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pgAssistant 2.8 — Deterministic PostgreSQL Analysis with the new Global Advisor
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A note from our sponsor - SaaSHub
www.saashub.com | 7 Jun 2026
Index
What are some of the best open-source Performance projects? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | Gin | 88,613 |
| 2 | pretext | 48,188 |
| 3 | Fiber | 39,815 |
| 4 | fastify | 36,365 |
| 5 | solid | 35,582 |
| 6 | sharp | 32,282 |
| 7 | k6 | 30,726 |
| 8 | leakcanary | 29,915 |
| 9 | locust | 27,871 |
| 10 | react-virtualized | 27,064 |
| 11 | {fmt} | 23,541 |
| 12 | gofr | 21,379 |
| 13 | ava | 20,853 |
| 14 | Atlas | 20,768 |
| 15 | DoraemonKit | 20,417 |
| 16 | lazysizes | 17,741 |
| 17 | million | 17,573 |
| 18 | Front-End-Performance-Checklist | 17,241 |
| 19 | inferno | 16,420 |
| 20 | tracy | 16,101 |
| 21 | Nuitka | 14,897 |
| 22 | systeminformer | 14,889 |
| 23 | nginx-admins-handbook | 14,148 |
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