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Apache Fluss (Incubating) – Streaming Storage for Real-Time Analytics

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Apache Fluss (Incubating) – Streaming Storage for Real-Time Analytics

Hey HN! On behalf of the Fluss community, I would like to share Apache Fluss (Incubating). Fluss is a next-generation streaming storage designed for real-time analytics. As a columnar streaming storage, it is the first of its kind and fills a significant gap in the current data management landscape [1]. In particular, Fluss aims to address the high costs and inefficiencies of current (row-oriented) streaming storage technologies and lakehouse architectures. Initially launched internally at Alibaba in July 2023, Fluss was open-sourced in November 2024 [2] and entered the Apache Incubator in June 2025 [3]. Since being open source, Fluss has received contributions from more than 60 developers across several companies and the community has been steadily growing. Currently, we are actively working towards the first release in the Apache Incubator. For more information on Fluss, please visit our website [4]. We sincerely invite everyone in the HN community to give Fluss a try and leave feedback here, on our mailing list [5] or on our Slack channel [6]. [1] https://fluss.apache.org/assets/images/img7-06886bca97977518... [2] https://www.ververica.com/blog/introducing-fluss [3] https://incubator.apache.org/projects/fluss.html [4] https://fluss.apache.org [5] https://fluss.apache.org/community/welcome/#mailing-lists [6] https://fluss.apache.org/community/welcome/#slack

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
83%83% predicted probability of success on Indie Hackers, 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, io · Missing: https docs, excited, just released
66%66% 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: slack, open · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
30%30% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
16%16% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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