Razorframe – a Node.js module for empowering real-time apps at scale

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https://github.com/team-emt/razorframe Razorframe is a Node.js library for enabling the effective backend scaling of your real-time application. Built on top of Socket.io, Razorframe’s simple server-and client-side API allows you to easily employ the task processing of multiple, parallel Node instances in conjunction with an in-memory queue. Our team set out to deliver on pushing the impact of real-time web through maximizing backend resources provided by multi-core server systems. By allowing your Node.js server to run on multiple threads and ensuring data consistency through an evented queueing system, Razorframe makes your application’s backend more resilient and performant under duress. We'd love to get some feedback on Razorframe and ways in which we can make it a better solution for your next Node.js project. Feel free to check us out on GitHub! Thank you!

Visit product View on Hacker NewsDec 20, 2016

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

73%73% 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.

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

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

nativeThis product was originally launched on this platform.

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

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

43%43% 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

40%40% 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

17%17% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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