31–40 of 106 posts
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
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.
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I think "written by genAI" should be a bigger turnoff than "written in Rust".
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
why? this is false in my opinion, iterating fast is not a good indicator of quality nor competitiveness
Overwhelmed by the sheer number of graph databases? I released a new site this week that lists and categorises them. https://gdb-engines.com
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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.
I'm turning off my brain and using neo4j
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
https://archive.fosdem.org/2025/schedule/event/fosdem-2025-5...
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…
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
> We've all seen open source projects drag on for 3 years without shipping anything, that's not necessarily better
There are more options than “never ship anything” and “use AI to slip 200,000 lines of code into a codebase”
Earlier quoted context omitted.
I think "written by genAI" should be a bigger turnoff than "written in Rust".
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
From examine this codebase it doesn’t appear to be written carefully with AI.
It looks like code that was promoted into existence as fast as possible.
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
Full history here: https://www.linkedin.com/pulse/brief-history-graphs-facebook...