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Cozo – new Graph DB with Datalog, embedded like SQLite

Hacker News

Cozo – new Graph DB with Datalog, embedded like SQLite

Hi HN, I have been making this Cozo database since half a year ago, and now it is ready for public release. My initial motivation is that I want a graph database. Lightweight and easy to use, like SQLite. Powerful and performant, like Postgres. I found none of the existing solutions good enough. Deciding to roll my own, I need to choose a query language. I am familiar with Cypher but consider it not much of an improvement over CTE in SQL (Cypher is sometimes notationally more convenient, but not more expressive). I like Gremlin but would prefer something more declarative. Experimentations with Datomic and its clones convinced me that Datalog is the way to go. Then I need a data model. I find the property graph model (Neo4j, etc.) over-constraining, and the triple store model (Datomic, etc.) suffering from inherent performance problems. They also lack the most important property of the relational model: being an algebra. Non-algebraic models are not very composable: you may store data as property graphs or triples, but when you do a query, you always get back relations. So I decided to have relational algebra as the data model. The end result, I now present to you. Let me know what you think, good or bad, and I'll do my best to address them. This is the first time that I use Rust in a significant project, and I love the experience!

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425points
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Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, models · Missing: mac, agents, macos
83%83% 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 · Missing: supports, reddit linkedin, podcasting
75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · 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.
TrustMRRLess likely to generate early MRR · Strong signals: way · 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
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · 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.

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