Big Data doesn't always involve Hadoop and MapReduce. This is a point I have made before, and I probably won't shut up about it anytime soon. Hadoop is good for a lot, but it has a batch-oriented ...

When the Big Data moniker is applied to a discussion, it’s often assumed that Hadoop is, or should be, involved. But perhaps that’s just doctrinaire. Hadoop, at its core, consists of HDFS (the Hadoop ...

The demand for job skills related to data processing — NoSQL, Apache Hadoop, Python, and a smattering of other such skills — has hit all-time highs, according to statistics collected by tech job site ...

MapReduce was invented by Google in 2004, made into the Hadoop open source project by Yahoo! in 2007, and now is being used increasingly as a massively parallel data processing engine for Big Data.

Apache Hadoop has been the driving force behind the growth of the big data industry. You'll hear it mentioned often, along with associated technologies such as Hive and Pig. But what does it do, and ...

The new release of Sybase IQ expands support for in-database analytics, including a native MapReduce API, Predictive Model Markup Language (PMML) support, integration with Hadoop, and an expanded ...

In the vast universe of IT, data is categorized as being either structured or unstructured, from a macro perspective. Generation of unstructured data is orders of magnitude higher than that generated ...

Although not immediately obvious, C++ is used in Big Data along with Java, MapReduce, Python, and Scala. For example, if you’re using a Hadoop framework, it will be implemented in Java, but MapReduce ...

As a poster child for big data, Hadoop is continually brought out as the reference architecture for big data analytics. But what exactly is Hadoop and what are the key points of Hadoop storage ...

In a world of real-time data, why are we still so fixated on Hadoop? Hadoop, architected around batch processing, remains the poster child for big data, though its outsized reputation still outpaces ...