stagDB – Free and Open-Source database manager with instant branching

Hacker News

While leading tech for a fintech org where we built out a relatively large and complex project in django and celery backed by postgres, we often came up with testing situations that needed real-world data to work with. We created an in-house hacked together version of what is now stagDB using only docker and zfs. stagDB allows its user to create a database, load it with data to create a master, and then create as many clones as the underlying hardware may support. This is still version 0.0.1 of the product. Feedback is welcome.

Visit product View on Hacker NewsAug 20, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, dock, using · Missing: mac, agents, macos

79%79% 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.

Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

74%74% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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.

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

23%23% 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

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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