Teradata users love Teradata.
It’s a relationship that’s rarely found in the world of enterprise technology. And quite frankly, until you talk to enough of Teradata’s customers, it’s hard to believe it exists.
But last year at Teradata’s Partners user conference we witnessed it — not by talking to users the company had hand-picked for us to meet, but from conversations with the guys or gals who stood in front or behind us as we waited in lines for our morning joe, on the many long walks from the hotel to the conference center and at lunch, when we sat to chow-down with strangers. The folks we spoke to, almost without exception, professed their love for Teradata.
And we’re telling you this because it matters. A lot.
Making the Most of Data
After all, in the world of big data — where we’ll all soon be working — leveraging open source seems to be the way to go.
And Teradata’s goods, mind you, are mostly proprietary and a lot more expensive. Not only that, but some would even argue that Teradata doesn’t have a big data play it can call its own.
But let’s put that argument aside because here’s what they do have: a large community of committed users who trust the data warehouse powerhouse to deliver to them the analytics capabilities that they need to make their businesses beat the competition.
Whether it’s big data, fast data or some other kind of data …Teradata’s customers trust Teradata to provide them with what they need to make the most of their data.
That’s a nice position to be in if you’re Teradata, but it’s also not one you can take for granted. And Teradata certainly isn’t doing that.
In 2011, just after the buzz around big data began to go mainstream, Teradata purchased Aster. Aster is a big data analytics platform that leverages its patented SQL-MapReduce to parallelize the processing of data and applications and deliver rich analytic insights at scale.
But while Aster is great for many things, Hadoop is better for others, and the two used together, in some cases, might be even better.
In early 2012, Teradata hooked up with open source Hadoop platform provider Hortonworks to bring big, big data capabilities to its customers. It enables customers to store and process huge volumes and varieties of data that arrives at huge velocities and gets dumped into what Teradata and Hortonworks are calling a Data Lake.
The base of the data lake usually consists of Open Source Apache Hadoop, which, though it’s free for the taking, is not what many consider to be truly enterprise grade or easy to work with.
And while Hortonworks, with its Hortonworks Data Platform (HDP), has done a great deal to make its Hadoop distro leading-edge and more attractive to Enterprises, no Hadoop distro is as customer friendly and enterprise worthy as the Teradata solutions they’re using today.
Not only that, but no user really wants to spend time moving data around or even learning new interfaces when they love the ones they already use. And when it comes to training and support, working with a vendor they already know and trust, who knows their systems and how their company ticks is preferable. And companies want all of this without sacrificing the wins that big data and leveraging big data technologies like Hadoop and Aster, can potentially deliver.
All the Benefits, Without the Pain
Teradata understands all of this, so it's hooked up with Hortonworks to deliver HDP capabilities from within its own products and to deliver services like consulting, training and support around it.