PERFORMANCE ANALYSIS OF STORAGE PROBLEMS IN BIG DATA USING COLUMN ORIENTED NOSQL DATABASES APPROACH

Abstract

A column-oriented database management system stores data tables as segments of columns of data instead of rows, similar to relational database management systems. There has been a significant amount of excitement and recent work on column-oriented database systems. These databases show good performance of an order of magnitude better than traditional row-oriented database systems on analytical workloads such as those found in data warehouses, decision support, and business intelligence applications. The aim of this research work is to evaluate the two most commonly used column oriented databases in order to show their capability in tackling Big Data storage challenges. These databases are Cassandra and HBase. The databases are also compared in terms of insert, latency, reads and writes performance taking into consideration the typical workloads. The comparison allows users to choose the most appropriate database according to the specific mechanisms and application need, but in some features one outperforms other.