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Stanchion – Column-oriented tables in SQLite

Hacker News

Stanchion – Column-oriented tables in SQLite

Hello HN! I built stanchion to scratch my own itch. I have personal applications running on SQLite where I want to store log and metric data (basically forever) but don't want to add complexity by bringing in a new database or whole separate server. Some of these applications are running on a Raspberry Pi, where storage and compute are limited, but I still want data warehouse like capabilities. I envision stanchion being used in similar scenarios: on phones and resource-limited devices in applications that are already using SQLite. I know that there are alternatives like DuckDB (which is very cool), but I want stanchion to be "good enough" that it is useful without having to add whole new database technology. If you think stanchion may be a good fit for your use case and you are interested in contributing, please test it and provide feedback by opening issues for any bugs, difficulties, or missing features you would need! Ideas are also welcome in this thread or as a github issue. Of course stars are always appreciated as well. The CONTRIBUTING doc in the repository has more details. - Dan

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, using, open · Missing: mac, agents, macos
82%82% predicted probability of success on Product Hunt, 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: ide, 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: para, ios · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios, personal, way · Missing: mobile apps, entrepreneurs, apps
36%36% 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
14%14% 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.

Correct prediction on native model

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