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Eating our own tails
If we are able to build mountains of code in days instead of months. Then we don't need 100 developers per app, but just a handful…. say 7. If we only need those 7, then we only need to buy 7 AI subscriptions. If we only buy 7 subscriptions instead of 100
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The Logic Graph Epiphany
By the end of this blog post, you are going to experience two epiphanies about databases. However, you are going to have to do a little more work than just read. You are going to have to stop and actually think about what you're reading. I promise it will
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You're working like a caveman she said.
A couple of weeks ago, Helene looked at me hunched over on my computer and said "You're working like a caveman". She is a bigwig in her company and her team does things I can't share that we will call "AI stuff". What she meant was that I was still loving
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Hey Database! Go Fine Tune Yourself
Everyone expects AI prices to go down in the long term. But in the short term, we have three things going on. Token prices keep dropping, hurray for that. Subscription fees are going up and dumping their all you can eat plans for volume based pricing. The
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Extending MySQL with VillageSQL
One of the things that made me fall head over heals for Neo4j so many years ago was just how extensible it was. If the database engineering team was busy rebuilding the clustering feature for the third time and didn't have time to take care of my feature
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Decision Graphs
About eight years ago, I wrote a little blog post on dynamic decision trees. If you have the time, go back and read that and the follow up posts on the subject. If not, I'll summarize. Instead of building a Rules Engine to make decisions, I built a dynami
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Improving Performance with Flame Graphs
Yes, I'm slowly but surely getting on the generative AI bandwagon. The eye catching image above was generated in Lexica, it's not perfect but our mind tricks us into accepting it. I am not a fan of asking these new AI systems questions and getting answers
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Counting Triangles
Our last post was about a Triangle Count query. It referenced another blog post from Kuzu where they explained their use of a Multi Way Join Algorithm to count 41 million triangles in 1.62 seconds. Using only binary joins it would take them 51.17 seconds
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All of NoSQL is because of this…
In this blog post, KuzuDB creator Semih Salihoğlu makes the case that graph databases need new join algorithms. If you've read the blog post and came away still a bit confused then look at the image above. This image shows what happens when you try to joi
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Bullshit Graph Database Performance Benchmarks
Hey HackerNews, let me just drop my mixtape, checkout my soundcloud and "Death Row" is the label that pays me. How is the Graph Database category supposed to grow when vendors keep spouting off complete bullshit? I wrote a bit about the ridiculous benchma
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