CozoDB, Hybrid Relational-Graph-Vector Database

Hacker News

Hi HN! We're thrilled to share CozoDB v0.6, a monumental update to our FOSS database, which already unifies relational and graph features. With the addition of vector search, CozoDB becomes an even better companion for LLMs like ChatGPT. This release introduces vector search using HNSW indices within Datalog, enabling seamless integration with powerful features such as ad-hoc joins, recursive Datalog, and classical whole-graph algorithms. This update significantly broadens CozoDB's capabilities. Check out the linked release note for an in-depth look at the new features, comparisons to other systems, and intriguing AI development possibilities. We'd love for you to take a look! I'll be here to answer any questions you might have. Looking forward to your feedback!

Visit product View on Hacker NewsApr 20, 2023

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

89%89% 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

71%71% 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

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

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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