Performance analysis of databases of different types and architectures

Abstract

The purpose of this work is to analyze the features of data storage and processing and to study the performance of modern information systems. The methodology for solving the stated task involves conducting a comparative analysis of the architecture and performance indicators of various system configurations used for data storage and processing that utilize Big Data, Cloud, and Grid technologies. The paper analyzes the architecture and examines the performance of modern data storage and processing systems depending on different architectures and types of databases. As a result of the conducted research, it was demonstrated—using relational databases with various configurations such as the Oracle DBMS and the column-oriented database HBase—that despite the shortcomings of column-oriented databases, their data access speed is higher due to their architecture. However, since column-oriented databases have significant disadvantages, namely, the lack of support for transaction processing and integrity constraints, their scope of application is quite limited. The results of this work can be used for the implementation of an efficient Hadoop Big Data, Grid, or Cloud system