Open-source version control for game development

Hacker News

Hi! I'm developing an open-source version control system for game developers called Jamsync. Jamsync aims to replace closed-source products like Perforce and PlasticSCM (now Unity DevOps) which are too expensive and complex for many developers. Current open-source systems like Git and Subversion do not scale with large projects or large files that are used in game development. Also, open-source systems do not support many workflows that designers, artists, and developers need to collaborate efficiently. Jamsync aims to create an open API for developers to integrate into their applications to enable collaboration on binary files in software such as in game engines and CAD. Jamsync still early in development, but you can push, pull, branch, and merge, like you would in a normal version control system. It's currently around 2x-10x faster than Git. https://jamsync.dev has more details and is a hosted alpha version of the system. Let me know if you have any thoughts!

Visit product View on Hacker NewsMay 31, 2023

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

89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

73%73% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host, efficient · Missing: plus, platform, intuitive

18%18% 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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Incorrect prediction on native model

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