Dataphyre – The Ultimate PHP Framework

Hacker News

I built Dataphyre to scale from side projects to massive distributed systems without bloat or rewrites. It’s a modern PHP framework powering Shopiro, an international marketplace handling millions of lines of code and sub-30ms product page renders. Dataphyre includes async task support, a full templating engine with caching + SEO, a native CDN system, full-text search, A/B testing, a JSON-based unit test runner, and advanced security (proof-of-work anti-spam, 2FA, firewall). It’s modular, open-source (free for personal use), and battle-tested in production. No Laravel/Symfony required—just performance, clarity, and control. Contributions welcome!

Visit product View on Hacker NewsMar 29, 2025

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

89%89% 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: code, open · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

20%20% 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.

Correct prediction on native model

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