Deeb – a lightweight embedded JSON database written in Rust

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I’ve been working on Deeb — a tiny embedded database that stores your data as JSON files and behaves like an ACID-ish transactional database. It’s written in Rust and designed for small apps, side projects, experiments, or dev tools where spinning up Postgres or Mongo is overkill. It’s inspired by the flexibility of MongoDB and the simplicity of SQLite, but stores everything in plain JSON. That means you can open, inspect, and edit your data manually — or use the API to query and mutate it with transactions, associations, and nested queries. I just launched a new docs site and opened up a Discord community for discussion/feedback. Some of the early use cases people have shown interest in: • Local-first apps • Simple tooling dashboards • Quick mock APIs • Portable experiment storage • Drop-in database for internal dev tools If you want to see how it works, the code is here: https://github.com/The-Devoyage/deeb Would love to hear your thoughts — critiques welcome. Always looking to make this thing sharper.

Visit product View on Hacker NewsJul 21, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, new, tiny · Missing: mac, agents, macos

94%94% 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

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.

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

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

38%38% 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

26%26% 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

20%20% 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.

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