Samuel Kaspi

Work place: School of Engineering, Construction and Design (IT), Melbourne Polytechnic, VIC 3072, Australia



Research Interests: Computer Science & Information Technology, Information Systems, Information Retrieval, Multimedia Information System


Dr. Samuel Kaspi earned his PhD (Computer Science) from Victoria University, a Masters of Computer Science from Monash University and a Bachelor of Economics and Politics from Monash University. He is a member of Australian Computer Society (ACS) and Association for Computing Machinery (ACM).

Sam is currently the Information Technology Discipline Leader and Senior Lecturer of the School of Engineering, Construction & Design, Melbourne Polytechnic, Australia. Previously, Dr Kaspi taught at Victoria University, consulted privately and was the CIO of OzMiz Pty Ltd.

Sam has been active in both teaching and private enterprise in the areas of software specification, design and development. As chief information officer (CIO) of a small private company he managed the development and submission of five granted and three pending patents. He also managed the submission of a successful Federal Government Comet grant under the Commercialising Emerging Technologies category. He has also had a number of peer reviewed publications including the Institute of Electrical and Electronics Engineers (IEEE).

Author Articles
SQL Versus NoSQL Movement with Big Data Analytics

By Sitalakshmi Venkatraman Kiran Fahd Samuel Kaspi Ramanathan Venkatraman

DOI:, Pub. Date: 8 Dec. 2016

Two main revolutions in data management have occurred recently, namely Big Data analytics and NoSQL databases. Even though they have evolved with different purposes, their independent developments complement each other and their convergence would benefit businesses tremendously in making real-time decisions using volumes of complex data sets that could be both structured and unstructured. While on one hand many software solutions have emerged in supporting Big Data analytics, on the other, many NoSQL database packages have arrived in the market. However, they lack an independent benchmarking and comparative evaluation. The aim of this paper is to provide an understanding of their contexts and an in-depth study to compare the features of four main NoSQL data models that have evolved. The performance comparison of traditional SQL with NoSQL databases for Big Data analytics shows that NoSQL database poses to be a better option for business situations that require simplicity, adaptability, high performance analytics and distributed scalability of large data. This paper concludes that the NoSQL movement should be leveraged for Big Data analytics and would coexist with relational (SQL) databases.

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