Yaiko – A fullstack web framework for Rust and jQuery

Hacker News

Yaiko ( https://github.com/sazalo101/yaiko ) is an open-source fullstack web framework for Rust. Most Rust web libraries require assembling auth, sessions, CSRF, rate limiting, migrations, and a JS build pipeline separately. Yaiko packages these into a single framework using Rust on the backend and jQuery on the frontend, requiring no Node.js build steps. Features: Built on Hyper and Tokio (80,000+ RPS) Built-in SQLite and PostgreSQL migration runner (yaiko migrate run) CSRF, rate limiting, WebSockets, and background job queue Scaffolding CLI (cargo install yaiko) Documentation: https://github.com/sazalo101/yaiko/blob/main/BOOK.md Crates.io: https://crates.io/crates/yaiko Feedback on the API design and architecture is appreciated.

Visit product View on Hacker NewsJul 25, 2026

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2points

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: single, using, open · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: pipe, 000, io · Missing: https docs, excited, just released

61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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