NoSQL + Hadoop Without the Headaches: MapR Technologies Announces New Big Data Platform for HBase #stratany2012

Live from O’Reilly Strata Conference and Hadoop World: MapR M7 brings enterprise-grade reliability and performance to HBase, adding integrated snapshots, mirroring, instant recovery, and delivering consistent, low latency.

The Big Data Treasure Chest

Within most enterprises there sits a large and precious treasure chest. Inside that chest sits data which holds great, untapped value. While CEOs might have recognized this a few years back, they didn't talk about it much because it was impractical and near impossible to extract wealth from the data.

Not so much anymore. Hadoop’s speedy data processing and analytics capabilities have changed that dramatically.

Enterprises worldwide are now using, or plan to use, Hadoop to unlock the value in their big data stores. But doing so isn't simple and it’s not without risks. This has opened the door for vendors to add reliability, stability and host of bells and whistles to Hadoop. MapR is one of the companies that leads that space.

MapR Announces New Big Data Platform

This morning at the O’Reilly Strata Conference + Hadoop World 2012 MapR unveiled M7 which promises to bring unprecedented Hadoop and NoSQL capabilities together on an easy, dependable and fast platform. With MapR M7, Big Data operations ranging from batch analytics to real-time database functions can be performed with enterprise-grade reliability and protection.

“We've made Hbase enterprise grade,” says Tomar Shiran, director of product management at MapR, explaining that MapR M7 can withstand multiple software and hardware outages and keep applications running without needing any administrator intervention at all. It’s the only Hadoop distribution that provides instant disaster recovery and full data protection with snapshots and mirroring, he adds.

But MapR M7 doesn't stop there, it also provides constant and consistent performance at unprecedented levels because it doesn't require compactions and because its innovative data structures minimize the read- and write-amplification factor. Updates and inserts are also much faster.

“We start with Hadoop and by adding our own innovations we make it much better,” says Shiran. 

MapR & the Google Compute Engine, Plus More

And while we know that every vendor has a pitch to explain why they are the best, MapR points to its recent wins. They snagged an exclusive to run Hadoop services on the Google Compute Engine last June, which says a lot because Google wrote the paper on Map Reduce. In that same month, Amazon announced that MapR’s Hadoop distributions would be available on Amazon Web Services vs. its own Elastic MapReduce service that runs on Apache Hadoop.

MapR has other impressive enterprise level Big Data ground-breakers on its client list as well, such as the Rubicon Project, a digital advertising infrastructure company that automates buying and selling for the global online advertising industry; Ancestry.com which crunches human genome, text and other data to lead you to your ancestors, and many, many others.

MapR is setting a new benchmark in the world of Enterprise-grade Hadoop. It will be interesting to see if anyone is able to exceed it before it “bests” itself.

 

 

Source : cmswire[dot]com

Alpine Data Labs Offers Browser-based Predictive Analytics for Hadoop

Alpine Data Labs has announced Alpine 2.8, a new predictive analytics platform that work with Hadoop - straight from your browser.

If your company is typical, it’s thriving in this age of Big Data. You’ve found Predictive Analytics to be a cakewalk. Your marketing department knows exactly which promotion to push at precisely which customer at what time of day, to the second. And your inventory managers know which products to store at which warehouse so that just-in-time replenishment actually happens just in time. Everything truly is just off the truck, just out of the oven, just off the vine…and so on.

Your CEO is as pleased as Martha Stewart on Pinterest. Big Data has truly lived up to its promise of improving operations, capitalizing on new opportunities and driving new revenue.

NOT. Or not yet, anyway.

“Big Data is really, really hard,” says Steven Hillion, Chief Product Officer of Alpine Data Labs, whose mission it is to provide its customers with a reliable, cost-effective way to apply predictive analytics to Big Data.

“It doesn’t have to be that way,” he adds.

Leveraging Hadoop for Predictive Analytics

And it’s with that thought in mind that Alpine Data Labs is today introducing Alpine 2.8, the industry’s first predictive analytics platform that leverages the full power of Hadoop, enabling enterprises to finally harness the promise of Big Data. With this advance, Alpine 2.8 users will be able to perform end-to- end analytics on combined data from Hadoop and relational databases, all from the ease of their web browser.

This should spell a welcome relief to the large number of companies and other organizations who admit to be struggling with setting up big data infrastructures and/or working with samples that must be extracted from the Hadoop file system; Alpine Data Labs’ solutions are in-database.

But that’s far from the only win, companies who use Alpine 2.8 might be free of the burden of trying to hire staff with the sophisticated statistical and coding development skills Hadoop requires. “They may not have to write a single line of code,” says Arshak Navruzyan , Alpine’s Vice President of Product Management. “We make the promise of Big Data more accessible,” he adds.

And because using Alpine 2.8 is as easy as opening a browser, everyone from business analysts and data engineers can participate in predictive analytics and work together to share workflow and analyses and to discover important insights.

The promise of Big Data becomes less of a dream and more real.

Alpine 2.8 Highlights

Predictive Analytics and Data Mining on Hadoop

Provides end-to-end analytics workflows on data from Hadoop. Offers predictive modeling, data transformation and visualization of Hadoop datasets. Users can generate insights by performing statistical analyses and building scalable models on massive datasets without writing a line of code, using an intuitive interface. 

A Data Agnostic Approach to Analytics

Draw upon data from multiple sources, including HDFS and MPP databases. Explore tables and files without complex and time-consuming data movement, infer structure automatically and combine data from multiple sources. Use a single workbench and a common set of scalable operators that apply equally to Hadoop and relational data.

Expanded Web-Based Functionality

The web-based functionality greatly expands the product capabilities to offer full modeling and workflow creation capabilities with an improved look and feel. It simplifies workflow editing, provides full data browsing and visualization capabilities, and provides an accessible framework for the entire team to collaborate on advanced analytics.

Broadest Database Support

Alpine 2.8 supports databases Greenplum, Oracle 11g, Oracle Exadata, Netezza, DB2, and PostgreSQL. The Hadoop supported platforms are Apache Hadoop 0.20.2+, Greenplum GPHD 1.0+, and Cloudera CDH3.

 

 

Source : cmswire[dot]com