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Big Data Bits: The Strata Edition - Beyond Hadoop Distributions

Welcome back my friends to the show that never ends …

Even though we’ve left the Strata + Hadoop World conference held in New York City last week, the notable news we didn’t report keeps buzzing in our ears, reminding us that we need to share it with you.

We’ve picked out what we think is most relevant and interesting to our readers and we’re splitting it between two posts. This one, in traditional Big Data Bits style, covers product/service announcements; the next discusses what we found to be especially noteworthy from the presentations at the conference.

In case you missed last week’s coverage, check out the news made by Cloudera, EMC, Infochimps, MapR, Microsoft and SAP HANA (we covered Hortonworks and Pivotal the week before). With the exception of SAP and Infochimps, the aforementioned news centers around making Hadoop a better platform or data hub, as some will now be calling it. The announcements that follow seem to have a common theme: namely, they make Hadoop more palatable and accessible to the Enterprise and the Enterprise user.

Alteryx, Cloudera, Revolution Analytics Set You Up to Deliver Insights Like a Data Scientist

Alteryx COO George Mathew says that there are, at best, 200,000 data scientists in the world. Knowing this, the question remains how enterprises will leverage Big Data to its potential when the talent required to do so doesn’t ( yet) exist?

Some believe that putting aspiring data scientists through Big Data+Analytics “universities” and bootcamps is the answer.

Others, like Alteryx and Revolution Analytics, think that giving the 2.5 million data analysts in the world the tools they need to do the geekiest part of a data scientist’s job may be another.

It’s with this in mind that the companies created a technology that analysts and business users can use to easily create and run sophisticated predictive analytics directly on data stored in Cloudera's Distribution Including Apache Hadoop.

Continuuity Makes Big Data App Development Easier with Reactor 2.0 and Rackspace 

There’s something Continuuity founder Jonathan Gray takes to heart what a good many big data geeks might not; namely, that before big data application development can go mainstream, it has to get a whole lot easier. After all, not every engineer is a prodigy or has a degree from (or can even be admitted into) Stanford, UC Berkeley, Carnegie Mellon, IIT or MIT.

“Developing applications on top of Hadoop is really, really hard,” Gray told me last year, and he should know, he built real time services for Hadoop and Hive when he worked at Facebook.

In order to make development easier for others, Gray and the Continuuity team built Reactor, the fastest and easiest way to build and run Hadoop and HBase applications.

At Strata, Gray announced Reactor 2.0, which includes MapReduce Scheduling, High Availability, Resource Isolation and full REST API support. The company also hooked-up with Rackspace, which means that Reactor 2.0 is now available on the public cloud — which might bolster Rackspace's Hadoop as a Service offering.

Kognitio Delivers Rapid Return On Big Data

Hadoop wasn’t built for speed, but in-memory technologies are. Big data analytics company Kognitio, announced the availability of its new platform, Kognitio Analytical Platform 8.1 at Strata. Its In-MemorySM advanced analytical platform enables SQL access on top of Hadoop, delivering rapid return on insight from big data.


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