Where database blog posts get flame-broiled to perfection
Ah, yes. Another dispatch from the "move fast and break things" brigade, who seem to have interpreted "things" to mean the foundational principles of computer science. One reads these breathless announcements about "AI-powered vector search" and is overcome not with excitement, but with a profound sense of exhaustion. It seems we must once again explain the basics to a generation that treats a peer-reviewed paper like an ancient, indecipherable scroll.
Allow me to offer a few... observations on this latest gold rush.
First, this "revolutionary" concept of vector search. My dear colleagues in industry, what you are describing with such wide-eyed wonder is, in essence, a nearest-neighbor search in a high-dimensional space. This is a problem computer scientists have been diligently working on for decades. To see it presented as a novel consequence of "machine learning" is akin to a toddler discovering his own feet and declaring himself a master of locomotion. One presumes the authors have never stumbled upon Guttman's 1984 paper on R-trees or the vast literature on spatial indexing that followed. It’s all just… new to you.
I shudder to think what this does to the sanctity of the transaction. The breathless pursuit of performance for these... similarity queries... invariably leads to the casual abandonment of ACID properties. They speak of "eventual consistency" as if it were a clever feature, not a bug—a euphemism for a system that may or may not have the correct answer when you ask for it. "Oh, it'll be correct... eventually. Perhaps after your quarterly earnings report has been filed." This is not a database; it is a high-speed rumor mill. Jim Gray did not give us the transaction just so we could throw it away for a slightly better movie recommendation.
And what of the relational model? Poor Ted Codd must be spinning in his grave. He gave us a mathematically sound, logically consistent way to represent data, and what do we get in return? Systems that encourage developers to stuff opaque, un-queryable binary blobs—these "vectors"—into a field. This is a flagrant violation of Codd's First Rule: the Information Rule. All information in the database must be cast explicitly as values in relations. This isn't a database; it's a filing cabinet after an earthquake, and you're hoping to find two similar-looking folders by throwing them all down a staircase.
The claims of infinite scalability and availability are particularly galling. They build these sprawling, distributed monstrosities and speak as if they've repealed basic laws of physics. One gets the distinct impression that the CAP theorem is viewed not as a formal proof, but as a friendly suggestion they are free to ignore.
We offer unparalleled consistency and availability across any failure! One can only assume their marketing department has a rather tenuous grasp on the word "and." Clearly they've never read Brewer's conjecture or the subsequent work by Gilbert and Lynch that formalized it. It’s simply not an engineering option to "choose three."
Ultimately, this all stems from the same root malady: nobody reads the literature anymore. They read a blog post, attend a "bootcamp," and emerge convinced they are qualified to architect systems of record. They reinvent the B-tree and call it a "Log-Structured Merge-Trie-Graph," they discard normalization for a duplicative mess they call a "document store," and they treat foundational trade-offs as implementation details to be glossed over. Clearly they've never read Stonebraker's seminal work comparing relational and object-oriented models, or they wouldn't be repeating the same mistakes with more JavaScript frameworks.
There, there. It’s all very… innovative. Now, do try to keep up with your reading. The final is on Thursday.