In-memory data and compute on top of Hadoop

Hadoop gives us dramatic volume scalability at a cheap price. But core Hadoop is designed for sequential access - write once and read many times; making it impossible to use hadoop from a real-time/online application. Add a distributed in-memory tier in front and you could get the best of two worlds - very high speed, concurrency and the ability to scale to very large volume. We present the seamless integration of in-memory data grids with hadoop to achieve interesting new design patterns - ingesting raw or processed data into hadoop, random read-writes on operational data in memory or massive historical data in Hadoop with O(1) lookup times, zero ETL Map-reduce processing, enabling deep-scale SQL processing on data in Hadoop or the ability to easily output analytic models from hadoop into memory. We introduce and present the ideas and code samples through Pivotal in-memory real-time and the Hadoop platform.

Basic Introduction to Apache Hadoop

Hadoop lets you manage big data. In this Basic Introduction to Hadoop Video, gives the introduction to Apache Hadoop, including the roles of key and related technologies in the Hadoop ecosystem, such as: MapReduce, Hadoop Security, HDFS, Ambari, Hadoop Cluster, Datanode, Apache Pig, Hive, HBase, HCatalog, Zookeeper, Mahout, Sqoop, Oozie, Flume and associated benefits.



Source: http://www.youtube.com/watch?v=OoEpfb6yga8

What is Hadoop: SQL Comparison

Hadoop Video Training...

This video points out three things that make Hadoop different from SQL. While a great many differences exist, this hopefully provides a little more context to bring mere mortals up to speed. There are some details about Hadoop that I purposely left out to simplify this video.

What is Hadoop? - Vedio Tutorials

Below tutorial explains about how the Big Data is managed in live environment ? An Introduction to Hadoop. More explanation about Hadoop.

Learn how to use Hadoop with this Tutorial.