An enumerated analysis of NoSQL data models using statistical tools

An enumerated analysis of NoSQL data models using statistical tools

연구 분야: Databases

학회: Innovations in Systems and Software Engineering

The digital exploration of data in the modern technological world has paved the way for a new technology—big data. It is good for handling a massive volume and variety of data generated at high speed through online and offline transactions in different sectors. The NoSQL data model is often found more suitable for big data as it does not suffer from the limitations of traditional relational database (RDBMS) models. In this paper, the performance analysis of big data is done in an interesting way. The performances are evaluated using an experimental approach, taking a public data set of 5 million records and executing set of queries on different platforms like SQL Server 2012 (RDBMS) and two NoSQL models, Cassandra and MongoDB. Subsequently, the experimental results are verified by two well-known tools like Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and analysis of variance (ANOVA) to compare the performances from a practical perspective.