Sitalakshmi Venkatraman

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



Research Interests: Engineering


Dr. Sitalakshmi Venkatraman obtained doctoral degree in Computer Science, from National Institute of Industrial Engineering, India in 1993 and MEd from University of Sheffield, UK in 2001. Prior to this, she had completed MSc in Mathematics in 1985 and MTech in Computer Science in 1987, both from Indian Institute of Technology, Madras, India. This author is a Senior Member (SM) of IASCIT.

In the past 25 years, Sita's work experience involves both industry and academics - developing turnkey projects for IT industry and teaching a variety of IT courses for tertiary institutions, in India, Singapore, New Zealand, and more recently in Australia since 2007. She currently works as Lecturer (Information Technology) at the School of Engineering, Construction & Design, Melbourne Polytechnic, Australia.  She also serves as Member of Register of Experts at Australia's Tertiary Education Quality and Standards Agency (TEQSA). 

Sita has published eight book chapters and more than 100 research papers in internationally well-known refereed journals and conferences that include Information Sciences, Journal of Artificial Intelligence in Engineering, International Journal of


Business Information Systems, and Information Management & Computer Security. She serves as Program Committee Member of several international conferences and Senior Member of professional societies and editorial board of three international journals.  

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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