Apache ResilientDB, High-Performance Open-Source Blockchain

Hacker News

Hey Hacker News! We've been building Apache ResilientDB (incubating), a lightweight, modular, and high-performance open-source blockchain framework written in C++. Recently accepted into the Apache Incubator, ResilientDB is designed for flexibility, supporting various Byzantine Fault-Tolerant (BFT) and Crash Fault-Tolerant (CFT) consensus protocols, with native PBFT integration. With features like dynamic client-server architecture, robust checkpoint/recovery, and smart contract support, ResilientDB aims to push distributed ledger tech further. Check us out and join our community: Apache ResilientDB GitHub ( https://github.com/apache/incubator-resilientdb ). Would love your feedback!

Visit product View on Hacker NewsOct 28, 2024

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

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.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new, open · Missing: mac, agents, macos

44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

42%42% 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

32%32% 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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Correct prediction on native model

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