Scientists and mathematicians have long loved Python as a vehicle for working with data and automation. Python has not lacked for libraries such as Hadoopy or Pydoop to work with Hadoop, but those ...

Also featured in DataRush 5.0 is backing for newer languages on the JVM, including JRuby, Python, and Scala; users of these languages get parallel development capabilities.

Hunk is a relatively new product from Splunk for exploring and visualizing Hadoop and other NoSQL data stores. New in this release is support for Amazon’s Elastic MapReduce.

Hadoop 2.0 makes MapReduce less compulsory and the distributed file system more reliable. Written by Andrew Brust, Contributor April 5, 2012, 11:00 p.m. PT ...

To many, Big Data goes hand-in-hand with Hadoop + MapReduce. But MPP (Massively Parallel Processing) and data warehouse appliances are Big Data technologies too. The MapReduce and MPP worlds have ...

Apache Hadoop has been the driving force behind the growth of the big data industry. But what does it do, and why do you need all its strangely-named friends, such as Oozie, Zookeeper and Flume?

However, MapReduce should not be equated with Hadoop. MapReduce is just one of many ways to process your data in a Hadoop cluster. Spark can be used as an alternative.

Hadoop is the most significant concrete technology behind the so called 'Big Data' revolution. Hadoop combines an economical model for storing massive quantities of data - the Hadoop Distributed File ...

Hadoop MapReduce is still the best choice for batch processing of large amounts of data but for most other use cases, Spark is the better choice.

The Apache Software Foundation unveiled its latest release of its open source data processing program, Hadoop 2. It runs multiple applications simultaneously to enable users to quickly and ...