The Concepts Of Column Oriented Databases

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Abstract: This documents explores the concepts of column-oriented databases including its applications, advantages, and tools in which it is utilized. We describe how it differs from other database structures, and why it has become popular in the area of data analytics.


The ever-widening realm of big data has created an expanding frontier of exploration for the creation of new methods of data analysis in order to produce actionable knowledge for the benefit of organizations everywhere. Companies amass enormous troves of data every day. Keeping this data housed in a fashion that maximizes storage efficiency and in a format optimized for query and analysis is paramount for effective data warehousing. Many database structures exist for the storage, arrangement, and accessing of data, but large databases and online analytical processing (OLAP) benefit from specific qualities. In these databases, compression and rapid querying are the main enabling qualities sought for analytical data stores and data warehouses. Columnar (or column-oriented) relational databases (RDBMS) offer these and other benefits, which is why it is a popular database scheme for analytical systems. Specifically, the vertical arrangement of records is optimal for selecting the sum, average, or a count of total record attributes because one horizontal read yields all values of an attribute. Otherwise, a physical disk must seek over and past unwanted attributes of the records to provide the same

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