Ideas and quotes form original article by Guy Harrison on
Google’s algorithms have been implemented in the open source project Hadoop.
For certain workloads, MapReduce and Hadoop can outperform even the most expensive commercial RDBMS software and associated hardware – and can do so using much cheaper commodity hardware, and without expensive software licenses.
Hadoops main drawback is a simple interface.
Hive, developed at Facebook, provides a SQL-like interface to Hadoop. If you are familiar with SQL, you can submit a SQL statement to Hive that will then be compiled to MapReduce jobs executed by Hadoop.
Just as MapReduce has been pivotal at Google, Hadoop seems poised to become a critical technology in the wider world of data processing. MapReduce and Hadoop will never replace the relational database for all workloads, but, there is little doubt they represent an economically compelling alternative for many “big data” applications.