Where database blog posts get flame-broiled to perfection
Ah, yes, another dispatch from the wilds of industry, where the fundamental, mathematically proven principles of computer science are treated as mere suggestions. I must confess, reading the headline "Can databases fully replace them?" caused me to spill my Earl Grey. The sheer, unadulterated naivete is almost charming, in the way a toddler attempting calculus might be. Let us, for the sake of what little academic rigor remains in this world, dissect this... notion.
To ask if a database can replace a cache is to fundamentally misunderstand the memory hierarchy, a concept we typically cover in the first semester. It’s like asking if a sprawling, meticulously cataloged national archive can replace the sticky note on your monitor reminding you to buy milk. One is designed for durable, consistent, complex queries over a massive corpus; the other is for breathtakingly fast access to a tiny, volatile subset of data. They are not competitors; they are different tools for different, and frankly, obvious, purposes.
Apparently, the practitioners of this new "Cache-is-Dead" religion have also managed to solve the CAP Theorem, a feat that has eluded theoreticians for decades. How, you ask? By simply ignoring it! A cache, by its very nature, willingly sacrifices strong Consistency for the sake of Availability and low latency. A proper database, one that respects the sanctity of its data, prioritizes Consistency. To conflate the two is to believe you can have your transactional cake and eat it with sub-millisecond latency, a fantasy worthy of a marketing department, not a serious engineer.
They speak of "eventual consistency" as if it were a revolutionary feature, not a euphemism for "your data will be correct at some unspecified point in the future, we promise. Maybe."
What of our cherished ACID properties? They've been... reimagined. Atomicity, Consistency, Isolation, Durability—these are not buzzwords; they are the pillars of transactional sanity. Yet, in this brave new world, they are treated as optional extras, like heated seats in a car.
The breathless excitement over using a database for caching is particularly galling when one realizes they've simply reinvented the in-memory database, albeit poorly. Clearly they've never read Stonebraker's seminal work on the matter from, oh, the 1980s. They slap a key-value API on it, call it “blazingly fast,” and collect their venture capital, blissfully unaware that they are standing on the shoulders of giants only to scribble graffiti on their ankles.
Ultimately, this entire line of thinking is an assault on the elegant mathematical foundation provided by Edgar F. Codd. He gave us the relational model, a beautiful, logical framework for ensuring data integrity and independence. These... artisans... would rather trade that symphony of relational algebra for a glorified, distributed hash map that occasionally loses your keys. It is the intellectual equivalent of burning down a library because you find a search engine more convenient.
But I digress. One cannot expect literacy from those who believe the primary purpose of a data model is to be easily represented in JSON.