When processing in bulk, leading us to scale (that is, tens of billions of rows) we can trust Netezza to pull this off rather handily. With hardware and architecture in the bag for us, is there anything we can do wrong, or perhaps inefficiently, that would deny us entry to the soaring heights of performance so elusive on other platforms? After all, if the stratosphere is within reach, we want to go there as quickly as possible.
As it turns out, there are some things that Netezza doesn't do well. And all of them are transactional in nature. Not to worry, as we really don't want Netezza to foray into those realms. We can do it faster and simpler in set-based form. In fact, we find that many newbies have to shake off some transactional thinking that in later days they refer to as cobwebs. The trappings of transactional thinking that are artificial constraints, necessary evils to our existence on an SMP-based RDBMS (but are in our rear-view-mirror and rapidly fading once we cross over to Netezza)
Now don't get me wrong, many people will deploy an SMP-based RDBMS for their warehouses and have a smashing time of it for many years, perhaps far into the future with no scalability issues at all. We could even venture to assume that over half of all warehouses rolled out this way will likely never see a capacity hiccup, simply because they are rolled out firmly in the center of the "bell curve". (A little statistics lingo there)
Recall many years ago, in the prob&stat class we may have slept through, that the bell curve gives us the 80-20 rule or something akin to it. It also gives us a another rule, that twenty percent (or so) of warehouses will be at the small end, twenty percent at the top end, and the rest in the middle. So guess what? This puts eighty percent in the middle-of-the-road and not really on the Netezza radar for the moment. But perish the notion that Netezza intends to ignore that market. It plays very well in that zone too. In fact, Netezza can move-and-shake along the entire continuum of the solution spectrum.
But when it enters the upper twenty percent zone, the air starts to get thin. Nitrogen narcolepsy befalls the heroes-of-the-eighty-percent, and they start to fall away very quickly. When we get into the zone of searching, analyzing, crunching and even just summarizing data on the orders of billions, tens of billions, and hundreds of billions of rows, we have a number of additional rules that will impose themselves on our existence. These are no different than the laws of aerodynamics we would use to defeat the laws of gravitation. One set of rules has sway, while another set of rules is used to overcome the effect of the first. The rules we have to deal with are those concerned with scale. If we don't pay attention to scale, down to the lowest level possible, no amount of efficiency in software will bail us out. When it comes to scale, salvation is in the hardware. More importantly, the architecture of the hardware.
I often adjure prospective Enzees that when evaluating the TwinFin against other platforms, avoid the kool-aid softball questions that anyone can answer. When a proof-of-concept tournament is underway, the easy questions all float around in the eighty-percent zone where any of the technologies play in one form or another. Rather take a tough problem, one that only exists in the twenty-percent zone, and drop it in the lap of the tournament players. Take a look at three things: (1) what was the raw performance number, (2) what was the difficulty or complexity of the solution, (3) How many vendor engineers did it require and as a bonus (4) how long did it take the vendor engineers to give you an answer? Minutes, hours, days? How long they took to formulate an answer, and how many of them were required, is second only to the performance of the solution itself. After all, anyone can test-or-evaluate in the eighty-percent zone where everyone is a hero. Get the problem domain into the twenty-percent zone (where we'll be on day-one after the technology is installed) and get those answers now. Wouldn't it be a bit awkward to ask these questions when it's too late to do anything about it?
I have mentioned in other essays that the Netezza architecture, and its deep attention to details-of-scale are what come alongside us as our ally when the other heroes-of-eighty-percent simply gasp for air. One of these is the architecture of the disk drives themselves. The drives are of course dedicated to their own CPU, RAM, FPGA and all that, but the layout of the disk platter itself is also intriguing. As an aside, each Netezza disk shares information with another sister drive so that if it should crash, it can be hot-swapped and rebuilt from its sister drive very quickly, easily and automatically. So where is this drive data stored on the sister-drive? As the design would have it, on the inner rim of the sister drive's platter. Otherwise, each drive's outer rim holds user data and the middle ring holds temp space and system data. But we can see the wisdom in this model, that the outer rim is spinning fastest, so delivers the data to the user much faster than the inner rims would.
Does our eighty-percent-hero do this for us? Well of course not. The SMP-based model of Netezza's competitors share their drives like any other SMP device. The odd state of affairs is that they are shared-nothing at the functional level, but shared-everything at the hardware level. This dissipates the strength of the machine. Conversely for Netezza, it's shared-nothing all-the-way-down. This bodes well for query support, because it means every query gets the full-strength and undivided attention from the machine, even for the fractions of a second necessary to complete it, and thus each query is returned on a wave of strength, not a river of dissipation.
For those who want to roll out the eighty-percent models and be happy with it, hey I don't disparage anyone from making a living. Functionally speaking, those warehouses have some of the most advanced features on the planet - in the eighty-percent zone. Netezza's customers by definition have already breached the eighty-percent mark and will never revisit it again.
But true to form, when dealing with a non-scalable platform, our enemies rapidly reduce to size and complexity. That is, the larger the size of the solution, the less functionality we can derive from it. And the larger the complexity of the solution, its required storage capacity is stunted from growth. Guess what happens when we migrate either of these solutions to a Netezza machine? When the complex functionality is ported, it suddenly finds a breath of fresh air and data volumes start to grow, sometimes exponentially. If the data sizes are already too unwieldy and we move to Netezza, the additional capacity allows us to build more functionality which in turn leads to - you guessed it - even more growth of data volumes. The short answer is, when migrating or upgrading either of these animals, the new platform had better be able to immediately scale in orders of magnitude, not just incremental percentages. This is why so many migrations onto the eighty-percent-platforms sputter and fail. The initial migration is successful, but they quickly find themselves out of capacity in short order. This was never expected, so the migration is a bust.
But with Netezza, it has the capacity to take on the migrated functionality and grow with it - without any particular hiccups or worrisome meetings about its abilities. It just hums along, keeps all its promises and never complains.
Okay, so I'm a big fan of the technology. Mostly because it makes a migration easy and makes its customers happy. Who couldn't use a little more of that?
But for those heroes-of-the-eighty-percent, there's a place for them should they choose to don the necessary equipment for high-altitude flight. Of course, there aren't any heroes in the twenty percent zone, considering that the only true hero in that space is the TwinFin. And when flying above the clouds (with any technology), humility dictates that we set aside the hero-way - and we really have to trust the hardware, don't we?