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Big Data Bits: Big Data Empowered

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The analysts say that big data is maturing, that we’re no longer in an investigative mode and that instead we’re getting busy. Big vendors are buying start-ups to extend capabilities to their customers, we’re starting to run Hadoop on the Cloud, we’re using new databases to power activities we wouldn’t have dreamed of in the past, and so on. Want to know more? Read on … 

Teradata Goes Shopping

We don’t know why Teradata didn’t shout “Look what I bought, Ma” from the rooftops when it bought big data start-ups Revelytix and Hadapt earlier this month, but now we’re doing it for them.

The data warehouse leader has been busy strategically acquiring big data startups over the last several years, most notable among them, at least until now, is Aster. Now known as Teradata Aster, the big data analytics platform offers a patented SQL-MapReduce that parallelizes the processing of data and applications to deliver rich analytic insights at scale.

Hadapt does something complimentary. It’s an analytic platform that natively integrates SQL with Apache Hadoop to help customers analyze all of their data (structured, semi-structured and unstructured) in a single platform — no connectors, complexities or rigid structure.

Revelytix offers Loom, a data-management suite, that makes it easier to discover data, generate metadata and track data lineage.

Add those three acquisitions to Teradata’s Hadoop capabilities, developed in conjunction with Hortonworks, and you’ve got a pretty snazzy big data play to offer customers.

And Teradata’s customers love and trust Teradata. It might very well be one of the coziest vendor/ Enterprise relationships we’ve ever seen, so all that Teradata needs to do to keep its substantial market share is offer capabilities that compete with the upstarts.

MapR and AWS Make Hadoop on the Cloud Easy

Some companies don’t want to go through the pains of getting busy with Hadoop, and this is the case for a variety of reasons, says Jon Posnik, vice president of business development at MapR Technologies.

“There are those that want to get up quickly and experiment on the Cloud,” says Posnik, adding that once they discover that Hadoop is the way to go, they sometimes bring it in-house.

“Others do it vice versa,” he explains, meaning that they go to from hosting it internally and move to the cloud so that they can scale.

Still others take a good look at where their data is, and if it’s in the cloud, that’s where they work.

Starting today the cloud option becomes easier because MapR, and its Hadoop distro, is available on Amazon’s dropdown menu. Users can either use it as a fully integrated EMR service or through standard EC2.

It’s also worth noting that MapR, which stakes its claim on ease of use, might be a gentler path into Hadoop. Either way, the AWS option may be a good, less risky way to check it out.

Sorry Larry, Apache Cassandra Has Oracle Beat On This One

Sometimes we think that Open Source databases are chosen because they’re less expensive than something like Oracle, but other times older technologies simply can’t do the job.

They were built for different times and different use cases, Matt Pfeil of DataStax has told me more than once. As the co-founder of the company that develops solutions based on commercially supported, enterprise-ready Apache Cassandra, Pfeil generally points to customers like Netflix and eBay.

Late last week Datastax announced that Hulu leverages Cassandra’s distributed database management technology to store and provide real time access to subscriber watch history. Without that capability, Hulu customers wouldn’t have the benefit of a seamless viewing experience when switching from one device to the next.

Oracle Can Do SQL on Big Data

We don’t hear much about Oracle’s big data play, but rest assured they really do have one. Earlier this month they announced Oracle Big Data SQL, a nifty tool that extends Oracle SQL to Hadoop and NoSQL and provides the security of Oracle Database to all your data.

The big advantage to users is that data movement is minimized while breaking down silos.

What’s the downside? It can only run on Oracle’s Big Data appliance.

Title image by Farrukh (Flickr) via a CC BY-NC 2.0 license 

 
 
 
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