A Python-based, in-memory NoSQL database

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Over the last two weeks, I have been learning more about how NoSQL databases work. I decided to make a database, with the intent to use it on my personal website. JameSQL supports several query types, including and/or, range, span, and wildcard. It also has a text-based query language with support for operators that is transpiled back into a JSON query to be executed. You can try it out at: https://jamesg.blog/search-pages/?q=category_lower:%27indiew... Under the hood, I use a reverse index for text and boolean searches, a b-tree for range queries (using the btrees Python package), and a trie for string prefix queries (using the pygtrie package). Most queries are executed in < 0.01s.

Visit product View on Hacker NewsAug 24, 2024

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

65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

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: using · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

39%39% 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

37%37% 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

19%19% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

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