A Comparative Analysis of distributed databases for better performance, scalability, resilience and transactional integrity in the case of MOENCO

Abstract

There are several factors to consider when choosing the right database engine for an enterprise, and that depends to a large extent on the type of business   the data base is intended to serve. In the case of MOENCO S. Company, which is the main focus  of this research,   a number of factors  are considered, including cost (storage and writing charges in particular), where they value consistency over size, making it incredibly expensive, and ( speed over consistency which results in data discrepancy). When selecting a database management system, there will always be tradeoffs to consider, and one size does not fit all. However, there are new database products released that take a lot of inspiration from the NoSQL focus on performance, distribution and scalability and without throwing out all the relational features that have been useful for so many years. These products which include Google’s Cloud Spanner and Apache Ignite are sometimes referred to as NewSQL, replacing earlier products such as NoSQL that support ACID transactions instead of SQL queries, and generally following the relational database model while maintaining features oriented towards scaling and speed,   much more like the NoSQL products. 
The purpose of this paper is to conduct a comparative analysis of cutting-edge database technologies that adopt a multi-model approach and based on the analysis of findings   recommend a more viable database solution that is an open source, high performance, distributed database engine, and could serve better the achievement of the organization’s objectives while addressing the challenges at hand. This paper also addresses various challenges and benefits in implementing relational and non-relational 
(NoSQL) databases as well as address the designing factors in Distributed SQL databases like scalability, resilience, and transactional integrity across selected database engines and review of recent work.