ladybug

ladybugdb ( https://github.com/LadybugDB/ladybug ) appears to be an open source successor to Kuzu fwiw

There’s a fork https://github.com/LadybugDB/ladybug that you can use.

If you like kuzudb check out https://github.com/LadybugDB/ladybug

FYI LadybugDB is carrying on the Kuzu torch. https://github.com/LadybugDB/ladybug Cool project though! Very nice!!

Thank you for the shout out! I looked into your benchmark setup a bit. Two things going on: - Ladybug by default allocates 80% of the physical memory to the buffer pool. You can limit it. This wasn't the main reason. - Much of the RSS is in ladybug native memory connected to the python connection object. I noticed that you keep the connection open between benchmark runs. For whatever reason, python is not able to garbage collect the memory. We ran into similar lifetime issues with golang and nodejs bindings as well. Many race conditions where the garbage collector releases memory while another thread still has a reference to native memory. We now require that the connection be closed for the memory to be released. https://github.com/LadybugDB/ladybug/issues/320 https://github.com/LadybugDB/go-ladybug/issues/7 https://github.com/Lady

LadybugDB (https://github.com/LadybugDB/ladybug) at this point seems to be the only sustainable fork. When deciding what to do about the Kuzu archival on https://gdotv.com, we've gone with maintaining support for the last available version of Kuzu (it's still heavily used from what I'm seeing) whilst introducing support for LadybugDB. I've looked into a few other forks and at this point in time none seem to be actively maintained for more than a few weeks before getting dropped.

I maintain LadybugDB which implements WCOJ (inherited from the KuzuDB days). So I don't disagree with the idea. Just that it's a graph database with relational internals and some internal warts that makes it hard to compose queries. Working on fixing them. https://github.com/LadybugDB/ladybug/discussions/204#discuss...

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

Opensource Embedded Columnar Graph Database: https://github.com/LadybugDB/ladybug Store your graphs in Parquet files on object storage or DuckDB files and query them using strongly typed Cypher. Advanced factorized join algorithms (details in a VLDB 2023 paper when it was called Kuzu). Looking to serve externalized knowledge with small language models using this infra. Watch Andrej Karpathy's Cognitive Core podcasts more details.

It's interesting to see people use the term "GQL" to refer to GraphQL. https://www.gqlstandards.org/ is an ISO standard. The Graph Database people don't love search engine results when they're looking for something. I maintain a graph database where support for GQL often comes up. https://github.com/LadybugDB/ladybug/issues/6

Love the DuckLake spec. Now there is something similar for Graphs. https://adsharma.github.io/graph-archiving/ https://adsharma.github.io/beating-the-CAP-theorem-for-graph... The catalog is based on the now archived kuzu graph db project. Development continuing here: https://github.com/LadybugDB/ladybug

The code to implement this was open sourced today: https://github.com/LadybugDB/ladybug/pull/3