New Combined OLTP/OLAP RDBMS with Native ML on Kubernetes

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Hi HN, I am Monte Zweben, co-founder of Splice Machine (https://www.splicemachine.com), a database company striving to make it really easy to build operational applications that take full advantage of big data and machine learning. Our mission is to make distributed data management and ML accessible to all. We invite you to give our new Kubernetes version a try at cloud.splicemachine.io. Our ask? For you to try our new solution —free — and share your thoughts. You can find all the details about why we created Splice Machine, what the product entails, and how exactly it works on this blog: https://medium.com/@mzweben/why-we-built-splice-machine-4a910732ef5e?sk=bfc1c5391ca90a1fc29dc9547854941a

Visit product View on Hacker NewsMay 27, 2020

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

69%69% 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 · Strong signals: created · Missing: supports, reddit linkedin, podcasting

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

53%53% 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

47%47% 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

45%45% 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

15%15% 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.

Incorrect prediction on native model

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