Where database blog posts get flame-broiled to perfection
Ah, another dispatch from the front. It’s always heartening to read these post-summit summaries. Really captures the... spirit of the thing.
It's so true, the energy in the room at these events is something special. It’s the kind of electric-yet-frayed energy you only get when you put a hundred people in a room who have all been woken up at 3 a.m. by the same creatively-implemented feature. They do care deeply. They care deeply about their pager not going off, about that one query plan that makes no logical sense, and about when, exactly, the "eventual" in "eventual consistency" is scheduled to arrive.
I love the phrase "exchanged ideas." It sounds so collaborative and forward-thinking. I can just picture it now. I’m sure the ideas exchanged were vibrant and productive. Ideas like:
...and left with a clear sense that we need to […]
Now that’s the part that really resonates. That palpable, shared, "clear sense." I remember that sense well. It’s the sense that the beautiful roadmap shown in the keynote has about as much connection to engineering reality as a unicorn. It’s the sense that the performance benchmarks in the marketing slides were achieved on a machine that exists only in theory and was running a single SELECT 1 query. It’s the sense that maybe, just maybe, bolting on another feature with regex-based parsing wasn't the shortcut we thought it was. We all knew where that particular body was buried, didn't we, folks? Section 4, subsection C of the old monolith. Good times.
But no, this is all just my friendly joshing from the sidelines. It's genuinely wonderful to see everyone getting together to talk about the future. It’s important to have these little pow-wows.
It’s just adorable. Keep at it, you guys. You'll get there one day. Just... maybe manage expectations on the "when."
I happened upon a missive from the digital frontier today, a so-called "SDK" for something named "Tinybird," and I must confess, my monocle nearly shattered from the sheer force of my academic indignation. It seems the industry's relentless campaign to infantilize data management continues apace, dressing up decades-old problems in the fashionable-yet-flimsy garb of a JavaScript framework. One is forced to document these heresies, lest future generations believe this is how we've always built things.
This preposterous preoccupation with defining datasources and pipes as TypeScript code is perhaps the most glaring offense. They celebrate this as an innovation, but it is nothing more than a clumsy, verbose abstraction plastered over the elegant, declarative power of SQL's Data Definition Language. They've traded the mathematical purity of the relational model for the fleeting comfort of a linter, conflating programmer convenience with principled design. It is a solution in search of a problem, created by people who evidently find CREATE TABLE to be an insurmountable intellectual hurdle.
Then they have the audacity to champion "type-safe ingestion." How quaint. Do they truly believe they've invented the concept of a schema? Forgive me, but we have had robust, database-enforced constraints and data types for half a century. This is merely application-level validation masquerading as a database feature, a fragile veneer of safety that pushes the burden of integrity away from the data store itself. One shudders to think what they've done to the 'C' and 'I' in ACID, likely replacing them with 'Convenience' and 'Inevitable Inconsistency.'
The promise of "autocomplete for queries" is presented as a gift from the heavens, but it is a digital pacifier for those who cannot be bothered to understand their own data structures. Codd's Fourth Rule specifies that the database description should be queryable just like any other data. If your developers need an IDE to hold their hand and guess which column comes next, you have not achieved "modern development"; you have achieved institutional incompetence. Clearly they've never read Stonebraker's seminal work on query processing; they'd rather have a machine guess for them.
And the pièce de résistance of this whole farce, the line that truly curdles the milk in my Earl Grey, is the claim that their command-line tool...
...feels like modern app development. My dear children, a database is not an "app." It is a rigorous, logical system for the preservation of truth. This desperate desire to make everything feel like a hot-reloading web framework demonstrates a terrifying disregard for the fundamental complexities of data. It’s as if the CAP theorem were merely a gentle suggestion one could "refactor" away with enough npm packages. Consistency, Availability, Partition Tolerance—these are not features to be toggled in a config file.
It seems the grand project of computer science has devolved from standing on the shoulders of giants to standing on the toes of toddlers, begging them for approval. They are not innovating; they are merely building shinier sandcastles on foundations of quicksand.
Alright, grab your free vendor t-shirts, folks, because I’ve just finished reading another blog post that’s going to make my on-call rotation so much more exciting. "MariaDB 12.3... reduces the number of fsync calls from 2 to 1." Wow. Groundbreaking. You solved a problem by... just putting the problem inside another problem. It's like my car is making two weird noises, so I fix it by welding the hood shut. Now there's only one, much more ominous noise. Innovation.
The whole premise here is a masterpiece of self-congratulation. "The performance benefit from this is excellent when storage has a high fsync latency." Let me translate that from Lab Coat to English: "If you're running your production database on a potato you bought on clearance, you're going to love this." My man, if your primary performance bottleneck is high fsync latency, you don't need a new binlog engine, you need to call your storage vendor and ask them why they sold you a platter of spinning rust from 2003. This isn't a best-case comparison; it's a cry for help.
And the honesty is just... chef's kiss. "My mental performance model needs to be improved... the improvement is larger than 4X." You don't say. You thought doubling your efficiency would give you a ~2X speedup, but it gave you 4X? That's not a sign of a revolutionary feature. That's a sign that your initial setup was so fundamentally broken that any change looks like a miracle. That's like saying, "I guessed that taking the parking brake off would make my car a little faster, but wow, it's a lot faster! My model needs to be improved!"
I see we’re benchmarking this revolution on an "ASUS ExpertCenter PN53." An ExpertCenter? Is that from the Best Buy "Pro-gamer" collection? You're testing a core database function on something I'm pretty sure my nephew uses to play Fortnite, with one whole NVMe drive. No RAID, no SAN, no enterprise-grade anything. And the benchmark? Oh, this is the best part.
The benchmark is run with 1 client, 1 table and 50M rows.
One client. One. Let that sink in. You’ve successfully simulated the exact workload of a high school student's first PHP project. Meanwhile, I'm over here dealing with 10,000 concurrent connections from a fleet of microservices all trying to update the same six rows during a flash sale. But sure, your 4X improvement with a single, polite client is definitely applicable. Definitely.
But let's skip the fantasy numbers and get to the part I live and breathe: the 3 AM holiday weekend reality. The part where the blog post ends and my nightmare begins. You've now taken the binlog—the sacred, immutable record of every change, the one thing that can save my entire career when things go sideways—and you’ve jammed it into InnoDB. You’ve put your only disaster recovery mechanism inside the very thing it’s supposed to be recovering. It’s like storing your building's fire extinguisher inside the furnace.
What happens when InnoDB gets wedged? Not a full crash, just one of those fun, high-concurrency lockups where it stops responding but doesn't technically die. Before, I could at least look at the binlog on disk to see the last committed transaction. Now? The binlog is locked up inside the engine that's... well, locked up. My replicas are blind. My failover scripts are useless. My monitoring tools? Ha. You think anyone wrote a new check for "is the binlog, which is now an internal InnoDB table, accessible?" Of course not. The dashboard will be all green. It’ll just say QPS is zero. Everything is fine.
I can already picture the incident call. I'll be trying to explain to a VP why our entire database fleet is down because a performance optimization created a single, catastrophic point of failure. I'll be digging through iostat and vmstat logs like some kind of digital archeologist, because of course nobody thought to expose internal metrics for this new franken-log.
I've got a special drawer in my desk. It's full of stickers from defunct startups and "revolutionary" database technologies. TokuDB, Clustrix, RethinkDB... they're all in there. They all had a blog post just like this one, with big, impressive numbers from a benchmark that had nothing to do with reality.
So go ahead, enable binlog_storage_engine. I've already got a spot cleared in the drawer for MariaDB's sticker. It'll fit right next to the one that says "Web Scale."
But hey, great work. You made a number go up in a spreadsheet. That’s what really matters. I’m sure it’ll look great on a slide.
Alright, let's pull up a chair and our Q3 budget spreadsheet. I’ve just skimmed this… fascinating dissertation on a problem I believe my engineers solved years ago with something they called a "code review." It seems someone has spent a great deal of time and money trying to sell us a fire truck to put out a birthday candle. My thoughts, for the record:
First, I’m being told about a terrifying monster called the “Connection Trap.” Apparently, it’s what happens when you write a bad query. The proposed solution in the SQL world is to… add another table. The proposed solution in the MongoDB world is to… rewrite your entire data model. I just did some quick math on a cocktail napkin. The cost of a senior engineer spending 15 minutes to fix a bad JOIN is about $45. The cost to migrate our entire infrastructure to a new "document model" to prevent this theoretical mistake is, let's see... carry the one... roughly the GDP of a small island nation. I'm not seeing the ROI here.
The "elegant solution" proposed is to just embed data everywhere. They call this a "domain-driven design" within a "bounded context." I call it "making a thousand expensive copies of the same file and hoping no one ever has to update them." They even have the gall to admit it might create some slight issues:
It may look like data duplication... and indeed this would be undesirable in a fully normalized model... You don’t say. So, we trade a simple, well-understood relational model for one where our storage costs balloon, and every time a supplier changes their name, we have to launch a search-and-rescue mission across millions of documents. This isn’t a feature; it's a future line item on my budget titled "Emergency Data Cleanup Consultants."
And how do we handle those updates? With a query so complex it looks like an incantation to summon a technical debt demon. This updateMany with $set and arrayFilters is presented as an efficient solution. Efficient for whom? Certainly not for our balance sheet when we have to hire three specialist developers and a part-time philosopher just to manage data consistency. The article breezily mentions the update is "not atomic across documents," which is a wonderfully creative way of saying, "good luck ensuring your data is ever actually correct across the entire system."
Let’s calculate the “True Cost of Ownership” for this paradigm shift, shall we? We start with the six-figure licensing and support contract. Then we add the cost of retraining our entire engineering department to forget decades of sensible data modeling. We'll factor in the migration project, which will inevitably be 18 months late and 200% over budget. Then comes the recurring operational overhead of bloated storage and compute costs. And finally, the seven-figure emergency fund for when we discover that "eventual consistency" was corporate-speak for "frequently wrong." My napkin math shows this "solution" will have us filing for Chapter 11 by the end of next fiscal year.
Ultimately, this entire article is a masterclass in vendor lock-in disguised as academic theory. It redefines a basic coding error as a fundamental flaw in a technology they compete with, then presents a "solution" that requires you to structure your entire business logic around their proprietary model. Once you've tangled your data into this web of aggregates and embedded documents, extracting it will be more painful and expensive than a corporate divorce. You’re not just buying a database; you’re buying an ideology, and the subscription fees are perpetual.
Anyway, thanks for the read. I'll be sure to file this under "Things That Will Never Get Budget Approval." I have a P&L statement that needs my attention. I will not be returning to this blog.
Ah, yes, another masterpiece of technical storytelling. I just finished reading this, and I have to say, it’s truly an inspiration. A real testament to what’s possible when you pair a visionary engineering team with a nine-figure marketing budget. Replacing a 12-hour batch job with sub-second data freshness is the kind of leap forward that gets me so, so excited for my next on-call rotation.
It’s just beautiful. The sheer confidence in promising real-time analytics is something to behold. It reminds me of those old cartoons where the coyote runs off a cliff and doesn't fall until he looks down. "Sub-second" is a magical phrase, isn't it? It works perfectly in a staging environment with ten concurrent users and a dataset the size of a large CSV file. I’m sure that performance will hold up beautifully under the crushing, unpredictable load of a global user base. There’s simply no way a novel distributed architecture could have unforeseen failure modes, especially around consensus or data partitioning.
And the migration itself! I can just picture the planning meeting. Someone drew a simple arrow on a whiteboard from a box labeled "Snowflake" to a box labeled "Magic Real-Time Database." Everyone clapped. The project manager declared victory. They probably even used the term "zero-downtime migration," my absolute favorite work of fiction.
We all know what that really means:
I can see it now. It’s 3:15 AM on the Sunday of Labor Day weekend. My pager, which I thought was a figment of a nightmare, is screaming on my nightstand. The sub-second freshness has apparently soured, and the data is now several hours stale because the revolutionary new ingest pipeline has a silent memory leak and fell over. Who could have possibly predicted that?
And how will we know things are going sideways? Why, the beautiful, vendor-provided dashboard, of course! The one with all the green checkmarks that’s completely disconnected from our actual observability stack. We’ll get right on integrating proper monitoring. It’s on the roadmap for Phase Two, right after we’ve "stabilized the platform" and "realized the initial business value." I’m sure the lack of alerting on query latency, consumer lag, or disk I/O won't be an issue until then. It’s fine. Everything is fine.
This whole story gives me a warm, familiar feeling. I’ve already cleared a spot on my laptop lid for your sticker. It’ll go right between "FoundationDB" and that Hadoop distro that promised to solve world hunger but couldn’t even properly run a word count job. They all promise the world. I’m the one who inherits the globe when it shatters.
Anyway, thank you for this insightful article. It was a fantastic reminder of the glorious, inevitable future of my weekends. Truly, a compelling read.
I will now be blocking this blog from my feed to preserve what little sanity I have left. Cheers.
Alright, let's pour a cup of lukewarm coffee and review this... masterpiece of engineering. Another Tuesday, another performance benchmark that reads less like a business proposal and more like a ransom note for my budget. I’ve seen sales decks with more clarity, and those are written in crayon.
First, we have the setup. The author casually mentions they compiled twelve different versions of two separate open-source databases from source. Oh, wonderful. So the "free" part of "free and open-source software" just means it's free from any semblance of convenience. The sticker price is zero, but the true cost is a team of specialists who speak exclusively in config file parameters and spend their days on "artisanal, hand-compiled databases." Let's pencil in $450,000 for the salaries of the two wizards we'd need just to understand this setup, shall we?
Then we get to the meat. My ears perked up at this little gem: modern MySQL uses "2X more CPU per transaction" and has "more than 2X more context switches" than Postgres. I'm no engineer, but I know what "2X more CPU" means: it means my cloud provider sends me a fruit basket and a bill that looks like a phone number. So the "great improvements to concurrency" are subsidized by a cloud budget that will grow faster than my quarterly anxiety. Excellent value proposition.
And lest we think Postgres is our savior, the report notes that "Modern Postgres has regressions relative to old Postgres." Regressions. They're shipping new versions that are actively worse under certain loads. Let me get this straight. We invest engineering time to upgrade, validate the new system, and migrate the data, all for the privilege of a 3% to 13% performance drop. It's like trading in your 2012 sedan for a brand new 2024 model, only to find out it has a hand crank and gets eight miles to the gallon.
I particularly enjoyed the author's candor on their data visualization.
On the charts that follow y-axis does not start at 0 to improve readability at the risk of overstating the differences. My compliments to the chef. This is a classic trick I haven't seen since our last vendor pitch. They turn a 2% improvement into a skyscraper to distract you from the fact that their solution costs more than a small island. We're not measuring New Orders Per Minute here; we're measuring Total Cost of Ownership, and the only chart I care about is the one showing our burn rate heading toward the stratosphere.
So let's do some quick, back-of-the-napkin math on the "True Cost" of adopting one of these glorious, free solutions. We start at $0. We add the $450k for our new compiler-whisperers. We'll factor in a 100% increase in our cloud compute bill for the CPU-hungry option, let's call that another $200k annually. Add $150k for the migration consultants, because you know our team will be too busy reading the 800-page manual. Throw in another $75k for retraining and the inevitable "emergency performance tuning sprint" six months post-launch. That brings our "free" database to a cool $875,000 for the first year. The ROI is, and I'm estimating here, negative infinity.
Honestly, at this point, I think our budget would be safer on stone tablets.
Ah, a truly inspiring piece of visionary literature. It’s always a pleasure to read these grand prophecies about our utopian, AI-driven future. It’s like watching someone build a magnificent skyscraper out of sticks of dynamite and calling it “disruptive architecture.” I’m particularly impressed by the sheer, unadulterated trust on display here.
It's just wonderful how we've arrived at a point where you can give an AI "plain-English instructions" and just... walk away. That’s not a horrifyingly massive attack surface, no. It's progress. I'm sure there's absolutely no way a threat actor could ever abuse that. Prompt injection? Never heard of it. Is that like a new kind of coffee? The idea of giving a high-level, ambiguous command to a non-deterministic black box with access to your production environment and then leaving it unsupervised for hours... well, it shows a level of confidence I usually only see in phishing emails.
And the result? A "flawlessly finished product." Flawless. That’s my favorite word. It’s what developers say right before I file a sev-1 ticket. I’m picturing this AI, autonomously building the next generation of itself, probably using a training dataset scraped from every deprecated GitHub repo and insecure Stack Overflow answer since 2008. The code it generates must be a beautiful, un-auditable tapestry of hallucinated dependencies and zero-day vulnerabilities. Every feature is just a creative new way to leak PII. It’s not a bug, it’s an emergent property.
I love the optimistic framing that we’re not becoming butlers, but "architects." It’s a lovely thought. We design the blueprint, and the AI does the "grinding." This is a fantastic model for plausible deniability. When the whole system collapses in a catastrophic data breach, we can just blame the builder.
"We do the real thinking, and then we make the model grind."
Of course. But what happens when the "grinding" involves interpreting our "real thinking" in the most insecure way possible?
admin/password123 for maximum efficiency.customer-data-all-for-real-authorized-i-swear.This isn’t scaling insight; it's scaling liability. You think coordinating with human engineers is hard? Try debugging a distributed system built by a thousand schizophrenic parrots who have read the entire internet and decided the best way to handle secrets management is to post them on Twitter. Good luck getting that through a SOC 2 audit. The auditors will just laugh, then cry, then bill you for their therapy.
And the philosophical hand-wringing about "delegating thought" is the cherry on top. You're worried about humanity being reduced to "catching crumbs from the table" of a superior intellect? My friend, I'm worried about you piping your entire company's intellectual property and customer data into a third-party API that explicitly states it will use it for retraining. You're not catching crumbs from the table; you're the meal.
It's all a beautiful thought experiment, a testament to human optimism.
But the most glaring security risk, the one that truly shows the reckless spirit of our times, is right there at the very end. A call to subscribe to a free email newsletter. An unauthenticated, unmonitored endpoint for collecting personally identifiable information. You're worried about a superintelligence I can't even get past your mail server's SPF record. Classic.
Well now, isn't this just a precious little blog post. Took a break from rewinding the backup tapes and adjusting the air conditioning for the server room—you know, a room that could actually house more than a hamster—to read this groundbreaking research. It warms my cynical old heart to see the kids these days discovering the magic of... running a script and plotting a graph.
It’s just delightful how you’ve managed to compare these modern marvels on a machine that has less processing power than the terminal I used to submit my COBOL batch jobs in '89. An "ExpertCenter"? Back in my day, we called that a calculator, and we didn't brag about its "8 cores." We bragged about not causing a city-wide brownout when we powered on the mainframe.
And I have to applaud the sheer, unmitigated audacity of this little gem:
For both Postgres and MySQL fsync on commit is disabled to avoid turning this into an fsync benchmark.
Chef's kiss. That's a work of art, sonny. Disabling fsync to benchmark a database is like timing a sprinter by having them run downhill with a hurricane at their back. It's a fantastic way to produce a completely meaningless number. You might as well just write your data to /dev/null and declare victory. We used to call this "lying," but I see the industry has rebranded it as "performance tuning." We had a word for data that wasn't safely on disk: gone. We learned that lesson the hard way, usually at 3 AM while frantically trying to restore from a finicky reel-to-reel tape that had a bad block. You kids with your "eventual consistency" seem to be speed-running that lesson.
I'm particularly impressed by your penetrating analysis. "Modern Postgres is faster than old Postgres." Astonishing. Someone alert the media. Who knew that years of development from thousands of engineers would result in... improvements? It's a shocking revelation.
And the miserable MySQL mess? Finding that "performance has mostly been dropping from MySQL 5.6 to 8.4" is just beautiful. It’s a classic case of progress-by-putrefaction. They keep adding shiny new gewgaws—JSON support, "document stores," probably an AI chatbot to tell you how great it is—and in the process, they forget how to do the one thing a database is supposed to do: be fast and not lose data. You’ve just scientifically proven that adding more chrome to the bumper makes the car slower. We figured that out with DB2 on MVS around 1985, but it's nice to see you've caught up.
Your use of partitioning is also quite innovative. I remember doing something similar when we split our VSAM files across multiple DASD volumes to reduce head contention. We did it with a few dozen lines of JCL that looked like an angry cat walked across the keyboard, not some fancy-pants PARTITION BY clause. It’s adorable that you think you’ve discovered something new.
This whole exercise has been a trip down memory lane. All these charts with squiggly lines going up and down, based on a benchmark where you’ve casually crippled commit consistency, run on a glorified laptop. It reminds me of the optimism we had before we'd spent a full weekend hand-keying data from printouts after a head crash. You've got all the enthusiasm of a junior programmer who's just discovered the GOTO statement.
So, thank you for this. You’ve managed to show that one toy database is sometimes faster than another toy database, as long as you promise not to actually save anything.
Now if you'll excuse me, I've got a COBOL copybook that has more data integrity than this entire benchmark.
Alright, settle down, kids, let ol' Rick pour himself some lukewarm coffee from the pot that's been on since dawn and read what the geniuses have cooked up this time. "Relational database joins are, conceptually, a cartesian product..." Oh, honey. You just discovered the absolute, first-day-of-class, rock-bottom basics of set theory and you're presenting it like you've cracked the enigma code with a JavaScript framework.
Back in my day, we learned this stuff on a green screen, and if you got it wrong, you didn't just get a slow query, you brought a multi-million dollar IBM mainframe to its knees and had a guy in a suit named Mr. Henderson asking why the payroll batch job hadn't finished. You learned fast.
So you've "discovered" that you can simulate a CROSS JOIN. And to do this, you've built this... this beautiful, multi-stage Rube Goldberg machine of an aggregation pipeline. $lookup, $unwind, $sort, $project. It's got more steps than the recovery procedure for a corrupted tape reel. You know what we called this in 1985 on DB2?
SELECT f.code || '-' || s.code FROM fits f, sizes s;
There. Done. I wrote it on a napkin while waiting for my punch cards to finish compiling. You wrote a whole dissertation on it. It’s adorable, really. You spent four stages of aggregation to do what a declarative language has been doing for fifty years. But you get to use a dollar sign in front of everything, so I guess it feels like you're innovating.
And then we get to the real meat of the genius here. The "better model": embedding. You’ve just performed this heroic query to generate all the combinations, only to turn around and stuff them all back into one of the tables. You’ve rediscovered denormalization! Congratulations! We used to do that, too. We called it "a necessary evil when the I/O on the disk controller is about to melt" and we spent the next six months writing complex COBOL batch jobs to keep the duplicated data from turning into a toxic waste dump of inconsistency.
But you, you’ve branded it as a feature. "Duplication has the advantage of returning all required information in a single read." Yes, it does. It also has the advantage of turning a simple update into a nightmare safari through nested arrays.
updateMany for that with a fancy arrayFilters. That’s cute. You’ve just implemented a WHERE clause with extra steps and brackets.fit.code and change it everywhere.You’re creating data integrity problems and then patting yourself on the back for inventing clever, document-specific ways to clean up your own mess. We had a solution for this. It was called normalization. It was boring. It was rigid. And it worked.
But this part... this is the chef's kiss right here:
Unlike relational databases—where data can be modified through ad‑hoc SQL and business rules must therefore be enforced at the database level—MongoDB applications are typically domain‑driven, with clear ownership of data and a single responsibility for performing updates.
Bless your heart. You're saying that because you’ve made it impossible for anyone to run a simple UPDATE statement, your data is now safer? You haven't created a fortress of data integrity; you’ve created a walled garden of blissful ignorance. You've abdicated the single most important responsibility of a database—to guarantee the integrity of the data it holds—and passed the buck to the "application's service."
I’ve seen what happens when the "application's service" is responsible for consistency. I’ve seen it in production, at 3 a.m., with a terabyte of corrupted data. I've spent a weekend sleeping on a cot in a data center, babysitting a tape-to-tape restore because some hotshot programmer thought he was too good for a foreign key constraint. Your "domain-driven" approach is just a fancy way of saying, "we trust that Todd, the new front-end intern, will never, ever write a bug." Good luck with that.
And then you have the audacity to wrap it all up by explaining what a one-to-many relationship and a foreign key is, as if you're bequeathing ancient, forgotten knowledge to the masses. These aren't "concepts" that MongoDB "exposes as modeling choices." They are fundamental principles of data management that you are choosing to ignore. It’s like saying a car "exposes the concept of wheels as a mobility choice." No, son, you need the wheels.
So go on, build your systems where every service owns its little blob of duplicated JSON. It’s a bold strategy. Let's see how it works out when your business rules "evolve" a little more than you planned for.
Now if you'll excuse me, I've got a JCL script that's been running flawlessly since 1988. It probably needs a stern talking-to for being so reliable. Keep up the good work, kid. You're making my pension plan look smarter every day.
Oh, how wonderful. A “detailed account” of the outage. Let me just grab my coffee and settle in for this corporate bedtime story. I’m sure it’s a riveting tale of synergistic resilience failures and a paradigm-shifting learning opportunity. It’s always a “learning opportunity” when it’s my money burning, isn’t it? Funny how that works.
They start with a sincere-sounding apology for the “inconvenience.” Inconvenience? Our entire e-commerce platform was a smoking crater for six hours. That’s not an inconvenience; that’s six hours of seven-figure revenue flushed directly down a non-redundant, single-point-of-failure toilet. My Q1 forecast just shed a tear.
But my favorite part is always the "What We Are Doing" section. It's never just "we fixed the bug." Oh no, that would be far too simple and, more importantly, free. Instead, it’s a beautifully crafted upsell disguised as a solution. They talk about their new Geo-Resilient Hyper-Availability Zone™, which, by a shocking coincidence, is only available on their new Enterprise-Ultra-Mega-Premium tier. For a nominal fee, of course.
Let’s do some quick math on the back of this now-useless P.O., shall we? I seem to recall the sales pitch. It was a masterpiece of financial fiction. They promised a predictable, all-in cost that would revolutionize our TCO.
Let's calculate the real cost of this "revolutionary" database, what I like to call the Goldman Standard Cost of Regret.
So, the "predictable" $500,000 annual cost is actually $1.675 million for the first year, and a cool $1 million every year after that. And for what? So I can read a blog post explaining how they’re “doubling down on operational excellence.”
They had a chart in their sales deck, I remember it vividly. It had an arrow labeled "5x ROI" shooting up to the moon. My back-of-the-napkin math shows an ROI of approximately negative 200%. At this rate, their "solution" will bankrupt the company by Q3 of next year. It's a bold strategy for customer retention, I'll give them that. You can't churn if your business no longer exists.
We are committed to rebuilding the trust we may have eroded.
You didn’t erode my trust. You took it out behind the woodshed, charged me for the ammunition, and then sent me a bill for the cleanup. The only thing you're "rebuilding" is a more expensive prison of vendor lock-in, brick by proprietary brick.
Bless their hearts for trying. Anyway, I’m forwarding this post-mortem to legal and adding their blog's domain to my firewall. Not for security, mind you, but for the preservation of my fiscal sanity.