This story is from the category Computing Power
Date posted: 27/08/2009
As the amounts of data being stored by databases around the world enters the realm of the petabyte (the amount of data stored in a mile-high stack of CD-ROM disks), efficient data management is becoming more and more important. Now computer scientists at Yale University have developed a new database system by combining the best features of multiple approaches to create an open source hybrid system called HadoopDB.
Traditional approaches to managing data at this scale typically fall into one of two categories. The first includes parallel database management systems (DBMS), which are good at working with structured data that contain, for instance, tables with trillions of rows of data. The second includes the kind of approach taken by MapReduce, the software framework used by Google to search data contained on the Web, which gives the user more control over how the data is retrieved.
?In essence, HadoopDB is a hybrid of MapReduce and parallel DBMS technologies,? said Daniel Abadi, assistant professor of computer science at Yale and one of the system designers. ?It?s designed to take the best features of both worlds. We get the performance of parallel database systems with the scalability and ease of use of MapReduce.?
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