Hadoop MapReduce has been widely embraced for analyzing large, static data sets. New technology integrates a stand-alone MapReduce engine into an in-memory data grid, enabling real-time analytics on ...

While MapReduce is proprietary technology, the Apache Foundation has implemented its own open source map-reduce framework, called Hadoop.

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.

Distributed programming models such as MapReduce enable this type of capability, but the technology was not originally designed with enterprise requirements in mind. Now that MapReduce has been ...

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 ...

Hadoop in a post-MapReduce world Those familiar with MapReduce will wonder how Tez is different. Tez is a broader, more powerful framework that maintains MapReduce’s strengths while overcoming ...

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?

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.

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.