Linkwarden – An open source collaborative bookmark manager

Hacker News

Hey there HN! Meet Linkwarden, a fully self-hostable, open-source collaborative bookmark manager to collect, organize and archive webpages. Please also visit/star our GitHub repo [1]. Linkwarden was built using TypeScript and NextJS, backed by a PostgreSQL database for the lighter-weight data. The rest of the data can be chosen either to be stored on the filesystem, or stored on the cloud on Digital Ocean Space/AWS S3, the reason for the cloud storage solution was for the Cloud offering [2], we realized that the preserved webpages (archives) take up space pretty quickly and S3 was much more efficient for this task. On the front-end we used TailwindCSS for styling and Zustand for state management. You could either use our Cloud offering (with 14-day free trial) to directly support this project and experience Linkwarden, or you could self-host it on your own machine and have maximum flexibility. Feel free if you had any questions, we'll do our best to answer it. [1]: https://github.com/linkwarden/linkwarden [2]: https://cloud.linkwarden.app/register - Hosted in Digital Ocean's datacenter located here in Toronto, ON.

Visit product View on Hacker NewsJul 31, 2023

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

83%83% predicted probability of success on Product Hunt, 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: open source, filesystem, io · Missing: https docs, excited, just released

78%78% 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 · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

57%57% 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

47%47% 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

13%13% 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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