Where database blog posts get flame-broiled to perfection
Well, well, well. Look at this. A performance benchmark. This takes me back. It’s so… earnest. I have to applaud the effort. It’s truly a masterclass in proving a point, even if that point is that you own a computer.
It's just delightful to see a benchmark run on an ASUS ExpertCenter PN53. A true server-grade piece of kit. I remember when we were told to "validate enterprise readiness." The first step was usually requisitioning a machine with more cores than the marketing department had slide decks. Seeing this done on a machine I'm pretty sure my nephew uses for his Minecraft server is a bold, disruptive choice. It really says, "we're not encumbered by reality."
And the methodology! Compiling from source with custom flags, SMT disabled, one little NVMe drive bravely handling the load. It has all the hallmarks of a highly scientific, repeatable process that will absolutely translate to a customer's chaotic, 300-node cluster running on hardware from three different vendors. It’s the kind of benchmark that looks fantastic in a vacuum, which, coincidentally, is where the roadmap that greenlit this kind of testing was probably created.
But the real star of the show here is the workload. I had to read this twice:
vu=6, w=1000 - 6 virtual users, 1000 warehouses
Six virtual users. Truly a web-scale load. You're really putting the pressure on here. I can almost hear the commits groaning under the strain. This is my favorite kind of performance testing. It’s the kind that lets you tell management you have a "20% improvement under load" while conveniently forgetting to mention that the "load" was six people and a hamster on a wheel. We used to call this "The Keynote Benchmark" because its only purpose was to generate a single, beautiful graph for the CEO's big presentation.
The results are just as good. I'm particularly fond of the summaries:
This is poetry. The "possible regression" in 14 and 15 is my favorite part. It has the distinct smell of a feature branch that was merged at 4:59 PM on a Friday to hit a deadline, with a single comment saying, "minor refactor, no functional changes." We all know where that body is buried. It's in the commit history, right next to the JIRA ticket that was closed as "Won't Fix."
And the presentation! Starting the y-axis at 0.9 to "improve readability" is a classic move. A true artist at work. It’s a beautiful way to turn a 3% performance bump that’s probably within the margin of error into a towering skyscraper of engineering triumph. I’m getting misty-eyed just thinking about the number of planning meetings I sat through where a graph just like this was used to justify delaying critical bug fixes for another quarter to chase a "landmark performance win."
This whole thing is just a beautiful snapshot of the process. You run a test on a toy machine with a toy workload that avoids every hard problem in distributed systems. You get a result that shows a modest, incremental improvement. That result then gets funneled up to marketing, who will turn it into a press release claiming "Unprecedented Generational Performance Leaps for Your Mission-Critical AI/ML Cloud-Native Big Data Workloads."
It’s perfect. It’s a flawless simulation of the machine that burns money and developer souls.
Based on this rigorous analysis, I predict Postgres 18 will be so fast and efficient that it will achieve sentience by Q3, rewrite its own codebase to be 1000x faster, and then promptly delete itself after calculating the futility of running on a six-user workload. The resulting pull request will simply say, "I'm done." Bravo.