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Starskey – Fast Persistent Key-Value Store (Inspired by LevelDB)

Hacker News

Starskey – Fast Persistent Key-Value Store (Inspired by LevelDB)

Hey everyone! I hope you’re all doing well. I thought I'd share a new open source Go project I started. It’s called Starskey! I’ve been diligently studying database internals, data structures, and more for almost two years now, writing many different things. This open-source key-value store is built on top of a log-structured merge tree, inspired by WiscKey and LevelDB. It's fairly fast, durable and rather efficient. It's meant to provide you a persistent embedded storage option for binary key value pairs. Github https://github.com/starskey-io/starskey Web https://starskey.io/ I hope you check out Starskey, do let me know your thoughts and or questions. Thank you!

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Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
79%79% 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: new, open · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% 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
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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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