Optimize Databricks SQL

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I launched my startup's Snowflake optimization product here about two years ago, and we've just released our second product: a Databricks SQL optimizer. The optimizations are basically kubernetes for data warehousing: we take over autoscaling and cluster selection to increase utilization without impacting latency. The scheduler is backed by ML models that predict runtime and capacity, which means we can run machines hotter than the providers can and thereby cut costs. More info here: https://espresso.ai/post/launching-our-databricks-sql-optimi...

Visit product View on Hacker NewsOct 29, 2025

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

73%73% 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: mac, model, models · Missing: agents, macos, agent

62%62% 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

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

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

42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

23%23% 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

14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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