About MapReduce MapReduce is a programming model specifically implemented for processing large data sets. The model was developed by Jeffrey Dean and Sanjay Ghemawat at Google (see “ MapReduce ...

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 ...

Lack of multiple data source support – Current implementations of the Hadoop MapReduce programming model only support a single distributed file system; the most common being HDFS.

Cascading is a new processing API for data processing on Hadoop clusters, and supports building complex processing workflows using an expressive, declarative API.

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.

Based on Hadoop, MapReduce equips users with potent distributed data-processing tools Bottom Line You’ll want to be familiar with the Apache Hadoop framework before you jump into Elastic MapReduce.

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 ...

The core components of Apache Hadoop are the Hadoop Distributed File System (HDFS) and the MapReduce programming model.

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 ...