Everyone’s talking about Big Data, even your grandmother has probably heard of it. “I don’t much about it, but I know it’s important,” my 90-year old father-in-law told me when I brought it up in a conversation.
I bet he's not the only one still trying to figure it out. Then comes the big data appliance -- bring on the head swirling effects.
Everyone Talks About Big Data
Not too long after, my father in-law started presenting me with articles. Thus far he has pointed out that the New York Times says “ it (Big Data) will change the way we work and live”, that Time Magazine has called it “a hot topic in the business world these days”, and that Sears will be using it for competitive advantage.
It’s hard to believe that both trend spotting technology future thinkers O’Reilly Media and GigaOm held their inaugural Big Data Conferences in 2011. The hype has grown huge in a very short time. At the GigaOm conference last year some of the presenters were hoping that we’d be calling “Big Data” something other than Big Data by now. But, it seems that, be it good or bad, we’re stuck with the term. The same goes for all the metaphors around it, such as, “Big Data is the new oil” and that there’s gold in Big Data.
But what is Big Data (other than lots of data) Exactly?
There’s no shame in not having a good handle on it. And, if you can answer that, try explaining a “Big Data appliance”. And when it comes to all those Big Data vendor announcements that keep flying at us day after day and week after week, how is one different from the next? The vendors and technologists who build the products and services may have it all figured out, but as for the rest of us? Big Data solutions have yet to be purchased, let alone, implemented at most non-technology, non-Web 2.0 dependent companies.
“What the hell is Hadoop?” a VP of Finance at a Fortune 50 company recently asked me. It was going to be mentioned at a meeting he was going to and he had forgotten to look it up on Wikipedia. “I know it’s used for processing Big Data,” he said, “but do the letters stand for something? Is it an acronym?” (Hadoop got its name from its founder Doug Cutting, who named it after his son’s toy elephant.)
I realized that the guy who held the purse strings for a humungous, well respected company was only a half of a step ahead of my 90-year old father-in-law. At that point, I decided that the next time I wrote about a Big Data product, service or solution, I was going to lean on the vendor to tell me some definitions and explain why their product was different. Brian Christian, the co-founder and CTO of Zettaset, was kind enough to oblige while we talked about his company’s recent product introduction -- Zettaset’s First Fully Integrated Enterprise OS Hadoop Solution.
The first question I asked was “What exactly is Big Data?” Christian, like every other Big Data vendor of whom I’ve ever asked this question, was excited to answer it. “It’s not a specific amount of data,”
he explained, it’s what you have when you as an organization can no longer process more data than you already are; when you reach a point when what you’re doing, with the technology you have, is no longer adequate; when you realize you have a big data problem and it’s time to fix it.
The fix, in many cases, is Hadoop, or Apache Hadoop, as it’s properly called. Wikipedia says it “is a software framework that supports data-intensive distributed applications under a free license. It enables applications to work with thousands of computational independent computers and petabytes of data. Hadoop was derived from Google's MapReduce and Google File System (GFS) papers. In plain English, what Hadoop does is that it makes it possible to process huge amounts of data in a time and cost effective way. (We were able to process Big Data before Hadoop, but we usually didn’t because it cost too much and took too long.)
Christian likens Hadoop to a very powerful automobile engine that comes without the rest of the car. “It doesn’t have wheels, a seat, a windshield or even a steering wheel,” he says, “you have to go build those or buy those and put them together yourself.”
From Big Data to Big Data Appliances
So it follows that a Big Data appliance is a fully integrated plug-and-play Hadoop solution that enterprises can buy Vs. building it or configuring it on their own.
Christian’s company, Zettaset, announced, earlier this week, that through a collaboration with its business partners Red Hat and Hyve Solutions (a division of Synnex, a supply chain distributor of IT systems, peripherals, system components, software and networking equipment) it was introducing the first fully integrated Enterprise OS Hadoop solution. More simply stated, companies who want, or need, to work with Big Data can now drive off the lot with the whole car, with all the necessary features, safety and security built in.
“In the Hadoop community, there are a lot of wasted resources that go into figuring out what is the best configuration of hardware, operating system and Hadoop distribution for the best use case for the enterprise. There are a lot of wasted cycles, a lot of headaches and a lot of pain,” says Christian “This is the only turnkey solution on the market that contains a trusted hardware, OS and Hadoop solution that is reputable, stable and standardized – it takes the guesswork out of everything.”