SQLite Extensions Guide

Hacker News

We’ve just released an open-source project called sqlite-extensions-guide ( https://github.com/sqliteai/sqlite-extensions-guide ), and we’re looking for contributors. The goal is simple: become the go-to documentation on how to load and use SQLite extensions across different languages, frameworks, and operating systems. SQLite is everywhere, and extensions unlock a huge amount of power (custom functions, new data types, vector search, cryptography, etc.). But figuring out how to actually load them varies a lot depending on your environment — C, Python, Go, Node.js, iOS, Android, Linux, Windows, macOS, each has its own quirks. We’ve already added working examples and OS-specific instructions, but there’s a long way to go. We’d love contributions from developers.

Visit product View on Hacker NewsAug 26, 2025

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

85%85% 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, macos, new · Missing: agents, agent, cursor

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

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

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% 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

29%29% 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

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: crypto · Missing: web3, chat, cryptocurrency

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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