From Amazon to Splunk, here's a look at the big data innovators that are now pushing Hadoop, NoSQL and big data analytics to the next level.
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Hortonworks Takes A Conservative Approach To Hadoop Hortonworks is the youngest provider of Hadoop software and commercial support, but it's an old hand when it comes to working with the platform. The company is a 2011 spinoff of Yahoo, which remains one of the world's largest users of Hadoop. In fact, Hadoop was essentially invented at Yahoo, and Hortonworks retained a team of nearly 50 of its earliest and most prolific contributors to Hadoop.
Hortonworks released its first product, Hortonworks Data Platform (HDP) 1.0, in June. Unlike those from rivals Cloudera and MapR, Hortonworks' distribution is entirely of open source Apache Hadoop software. And while Hortonwork's rivals claim higher performance (MapR) or are shipping components that are not yet sanctified by Apache (Cloudera), Hortonworks says its platform is proven and enterprise-ready.
Hortonworks isn't leaving it up to others to innovate. The company led the development of the HCatalog table management service, which is aimed at the problem of doing analytics against the data in Hadoop. Teradata is an early adopter of HCatalog and a major partner for Hortonworks. Microsoft is another important partner, and it tapped Horton to create a version of Hadoop (since contributed to open source) that runs on Windows. With partners like these and its influential team of contributors, there's little doubt Hortonworks will be a big part of Hadoop's future.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business wonít wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.