Apache Hadoop is an open source software framework for data-intensive distributed applications originally created by Doug Cutting to support his work on Nutch, an open source Web search engine. To meet Nutch's multimachine processing requirements, Cutting implemented a MapReduce facility and a distributed file system that together became Hadoop. He named it after his son's toy elephant. Through MapReduce, Hadoop distributes Big Data in pieces over a series of nodes running on commodity hardware. Hadoop is now among the most popular technologies for storing the structured, semi-structured and unstructured data that comprise Big Data. Hadoop is available under the Apache License 2.0.
2. R
R is an open source programming language and software environment designed for statistical computing and visualization. R was designed by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand beginning in 1993 and is rapidly becoming the go-to tool for statistical analysis of very large data sets. It has been commercialized by a company called Revolution Analytics, which is pursuing a services and support model inspired by Red Hat's support for Linux. R is available under the GNU General Public License
3. Cascading
An open source software abstraction layer for Hadoop, Cascading allows users to create and execute data processing workflows on Hadoop clusters using any JVM-based language. It is intended to hide the underlying complexity of MapReduce jobs. Cascading was designed by Chris Wensel as an alternative API to MapReduce. It is often used for ad targeting, log file analysis, bioinformatics, machine learning, predictive analytics, Web content mining and ETL applications. Commercial support for Cascading is offered by Concurrent, a company founded by Wensel after he developed Cascading. Enterprises that use Cascading include Twitter and Etsy. Cascading is available under the GNU General Public License.
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