Grafeo – A fast, lean, embeddable graph database built in Rust (grafeo.dev)

106 points by 0x1997 5 hours ago

adsharma 3 hours ago

There are 25 graph databases all going me too in the AI/LLM driven cycle.

Writing it in Rust gets visibility because of the popularity of the language on HN.

Here's why we are not doing it for LadybugDB.

Would love to explore a more gradual/incremental path.

Also focusing on just one query language: strongly typed cypher.

https://github.com/LadybugDB/ladybug/discussions/141

tadfisher 3 hours ago

Is LadybugDB not one of these 25 projects?

adsharma 3 hours ago

LadybugDB is backed by this tech (I didn't write it)

https://vldb.org/cidrdb/2023/kuzu-graph-database-management-...

You can judge for yourself what work has been done in the last 5 months. Many short videos here. New open source contributors who I didn't know before ramping up.

https://youtube.com/@ladybugdb

Aurornis 3 hours ago

Does anyone have any experience with this DB? Or context about where it came from?

From the commit history it's obvious that this is an AI coded project. It was started a few months ago, 99% of commits are from 1 contributor, and that 1 contributor has some times committed 100,000 lines of code per week. (EDIT: 200,000 lines of code in the first week)

I'm not anti-LLM, but I've done enough AI coding to know that one person submitting 100,000 lines of code a week is not doing deep thought and review on the AI output. I also know from experience that letting AI code the majority of a complex project leads to something very fragile, overly complicated, and not well thought out. I've been burned enough times by investigating projects that turned out to be AI slop with polished landing pages. In some cases the claimed benchmarks were improperly run or just hallucinated by the AI.

So is anyone actually using this? Or is this someone's personal experiment in building a resume portfolio project by letting AI run against a problem for a few months?

jandrewrogers 3 hours ago

That is a lot of code for what appears to be a vanilla graph database with a conventional architecture. The thing I would be cautious about is that graph database engines in particular are known for hiding many sharp edges without a lot of subtle and sophisticated design. It isn't obvious that the necessary level of attention to detail has been paid here.

adsharma 3 hours ago

Are you talking about Andy Pavlo bet here?

https://news.ycombinator.com/item?id=29737326

Kuzu folks took some of these discussions and implemented them. SIP, ASP joins, factorized joins and WCOJ.

Internally it's structured very similar to DuckDB, except for the differences noted above.

DuckDB 1.5 implemented sideways information passing (SIP). And LadybugDB is bringing in support for DuckDB node tables.

So the idea that graph databases have shaky internals stems primarily from pre 2021 incumbents.

4 more years to go to 2030!

jandrewrogers an hour ago

adsharma 2 hours ago

justonceokay 3 hours ago

Yes a graph database will happily lead you down a n^3 (or worse!) path when trying to query for a single relation if you are not wise about your indexes, etc.

cluckindan an hour ago

adsharma 3 hours ago

ozgrakkurt an hour ago

Using a LLM coded database sounds like hell considering even major databases can have some rough edges and be painful to use.

gdotv 3 hours ago

Agreed, there's been a literal explosion in the last 3 months of new graph databases coded from scratch, clearly largely LLM assisted. I'm having to keep track of the industry quite a bit to decide what to add support for on https://gdotv.com and frankly these days it's getting tedious.

piyh an hour ago

I'm turning off my brain and using neo4j

aorth an hour ago

Figurative!

arthurjean 2 hours ago

Sounds about right for someone who ships fast and iterates. 54 days for a v0 that probably needs refactoring isn't that crazy if the dev has a real DB background. We've all seen open source projects drag on for 3 years without shipping anything, that's not necessarily better

natdempk 41 minutes ago

Serious question: are there any actually good and useful graph databases that people would trust in production at reasonable scale and are available as a vendor or as open source? eg. not Meta's TAO

cjlm 34 minutes ago

Serious answer: limiting to just Open Source: JanusGraph, DGraph, Apache AGE, HugeGraph, MemGraph and ArcadeDB all meet that criteria.

pphysch 30 minutes ago

Yeah: Postgres, etc.

When you actually need to run graph algorithms against your relational data, you export the subset of that data into something like Grafeo (embedded mode is a big plus here) and run your analysis.

cjlm an hour ago

Overwhelmed by the sheer number of graph databases? I released a new site this week that lists and categorises them. https://gdb-engines.com

dbacar 2 minutes ago

Did you generate the list using an LLM?

satvikpendem 4 hours ago

There seem to be a lot of these, how does it compare to Helix DB for example? Also, why would you ever want to query a database with GraphQL, for which it was explicitly not made for that purpose?

cluckindan an hour ago

The d:Document syntax looks so happy!

OtomotO an hour ago

Interesting... Need to check how this differs from agdb, with which I had some success for a sideproject in the past.

https://github.com/agnesoft/agdb

Ah, yeah, a different query language.

nexxuz an hour ago

I was ready to learn more about this but I saw "written in Rust" and I literally rolled my eyes and said never mind.

ComputerGuru an hour ago

I think "written by genAI" should be a bigger turnoff than "written in Rust".

andriy_koval an hour ago

alternative opinion:

* it is possible to write high quality software using GenAI

* not using GenAI could mean project won't be competitive in current landscape

quantumHazer 30 minutes ago

chuckadams 39 minutes ago

Too bad you don't do the same for commenting on HN.

measurablefunc 3 hours ago

This looks like another avant-garde "art" project.