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Scalable pan/zoom with easy authoring, arbitrary datatypes
Scalable pan/zoom with easy authoring, arbitrary datatypes
https://github.com/tracyhenry/Kyrix Open source MIT project from Turing award winner Michael Stonebraker. Seeking contributors.
Share cardActual performance
22points
14comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
19%19% predicted probability of success on BetaList, based on ML models trained on real launch data.
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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