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A Complete Guide to Overcoming Executives’ Concerns about Hadoop

April 13, 2014 by Michele Nemschoff
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Overcoming executives’ concerns about Hadoop.

CEOs are often critical of adopting new technology, and for good reason. New technology is expensive and all too often fails to come through and offer any real value to the company. This could present a challenge for IT managers who want to implement Apache Hadoop, the increasingly popular and cost-effective framework for large-scale, data-intensive deployments, into the company’s technology infrastructure.[read more]

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How Your Hadoop Distribution Could Lose Your Data Forever

March 27, 2014 by Michele Nemschoff

Hadoop distribution could lose your data forever.

Relational database users have long depended on foundational protection techniques, such as data replication and snapshots. Today, both are also implemented in standard Hadoop architectures. Their method of application and effectiveness, however, is not the same across distributions.[read more]

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How To Maximize Performance and Scalability Within Your Hadoop Architecture

March 13, 2014 by Michele Nemschoff

Hadoop.

One of the main reasons for moving away from a traditional database solution for managing data is to increase raw performance and gain the ability to scale. It may come as a surprise to you to know that not all Hadoop distributions are created equal in this regard.[read more]

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3 Big Hadoop Myths Dispelled

March 4, 2014 by Michele Nemschoff

Hadoop myths.

As with any new technological innovation, a lot of myths have been generated about Hadoop. At Strata + Hadoop World, held in NY at the end of October, Jack Norris, CMO of MapR, discussed three of those myths and how MapR dispels them.[read more]

7 Important Types of Big Data

February 26, 2014 by Michele Nemschoff
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Types of big data.

Big data is a term thrown around in a lot of articles, and for those who understand what big data means that is fine, but for those struggling to understand exactly what big data is, it can get frustrating. There are several definitions of big data as it is frequently used as an all-encompassing term for everything from actual data sets to big data technology and big data analytics.[read more]

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NoSQL Vs. RDBMS for Interactive Analytics: Leveraging the Right and Left Brain of Data

February 6, 2014 by Soren Riise
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NoSQL Vs. RDBMS.

Comparing NoSQL and relational databases is lot like comparing the left and right sides of the brain. Too much focus on structural differences and attributes can overshadow the fact that we’re stuck with both sides of the brain and we need both to make the best use of sensory data.[read more]

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How MapR’s M7 Platform Improves NoSQL and Hadoop

January 31, 2014 by Michele Nemschoff

MapR’s M7 platform.

M7 removes the trade-offs organizations typically face when looking to deploy a NoSQL solution. Here’s a look at how the M7 platform is making NoSQL and Hadoop easier, faster and more dependable. Since enterprises already have several disparate data systems, having the ability to unify NoSQL and Hadoop under a single scalable cluster eliminates data silos and provides administrative simplicity.[read more]

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8 Features of a True Enterprise-Grade Platform for Hadoop and NoSQL

January 30, 2014 by Michele Nemschoff

True enterprise-grade platform for Hadoop and NoSQL.

Businesses have several options when looking for a Hadoop and NoSQL solution. The advantage of using the right enterprise-grade solution is that it can provide the dependability, ease-of-use, and speed required for real production use.[read more]

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7 Ways Businesses are Leveraging Hadoop

January 25, 2014 by Michele Nemschoff

Leveraging Hadoop.

When you hear about Hadoop or Big Data, you probably think of large Internet companies, such as Google or Facebook. However, the use of Hadoop is not limited to large search engines or even Internet marketing. Take a look at seven striking examples of how businesses across many industries are leveraging Hadoop to reach multiple business goals.[read more]

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Can Big Data and Hadoop Feed the World?

January 24, 2014 by Michele Nemschoff

Feed the world.

It’s no secret that the world’s population is growing. In fact, by 2050 the world’s total population is expected to reach the 9 billion mark, and according to the United Nations’ Food and Agriculture Organization, food production needs to increase by 60 percent by 2050 in order to keep up with population growth.[read more]

NoSQL, NewSQL and NuoDB

November 20, 2013 by Barry Devlin

A flexible database? That works?

The concept of emergent behavior (the idea that the database could be anything anybody wanted it to be, with SQL simply as first model) was interesting technically but challenging in positioning the product. Version 2 is more focused, with a tagline of distributed database and an emphasis on scale-out and geo-distribution within the relational paradigm.[read more]

The Total Cost of Big Data Performance [VIDEO]

June 25, 2013 by Mark van Rijmenam

Damien Black, CEO of SQLStream

During GigaOM Structure in San Francisco, Damien Black, CEO of SQLStream, explains the different costs of the most important data storage possibilities from this moment: Stream Processing, Relational Database and Hadoop Platforms.[read more]

The Road to Success with Big Data: A Closer Look at Expectations vs. Reality

June 8, 2013 by Farnaz Erfan

Big Data road to success

Big Data is complex. The technologies in Big Data are rapidly maturing, but are still in many ways in an adolescent phase. With all the hype around big data, it is easy to expect Hadoop to do anything and everything. However, the road to success with Hadoop is full of both opportunities and obstacles.[read more]

Data Variety: What It's All About

May 14, 2013 by Ling Zhang
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data variety / shutterstock

Data variety stands out from the three Vs of big data from the report of the big data survey conducted by NewVantage Partners in 2012. One of the survey results shows companies focusing more on data variety instead of data volume both now and in the next three years.[read more]

Real-Time Access to SaaS Data

May 8, 2013 by Gadi Yedwab

Data stored in SaaS applications is often inaccessible to BI tools. This is a major headache to early adopters of SaaS applications. With on-premise applications, IT departments can bypass the application and access data directly from the underlying database.[read more]