Abstract
Relational database management system was a popular choice for any kind of software development and design projects from its invention. The future of RDBMS is definitely graph databases with a NOSQL approach that goes beyond the relational model. Relational databases were extensively used for different kinds of data storage purposes. However, the increase in complex and interrelated data has revealed the limitations of relational database models. This paper examines the reconstruction process of transforming relational data into a graph database to overcome these limitations. We discuss the different types of graph databases evolved and explain how to migrate data in different models and methodologies. Because of the features of SQL and the powerful products of RDBMS, it is necessary to re-engineer traditional databases to NOSQL (non-SQL or non-relational) methods. Many software companies and research centres are trying to rebuild their legacy of RDBMS systems in NOSQL which can store different data as nodes, edges and relationships. Therefore, systems developed earlier in legacy systems need to be integrated with some methodologies in NOSQL which is a challenge for every business and organization.
Author served 30 years in India. Role played as Ex-Asst. Prof, Ex-IBM, Ex-AT&T, Ex-INCAT, Ex-Tata Technologies, Ex-Tata Motors), M.Tech (IIT, KGP, Computer Science and Engineering), B.E (Electronics and Telecommunication 1990), 6-Sigma Green Belt.
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Bhattacharyya, A., Chakravarty, D. (2024). Graph Database: Re-engineering Methodologies Relational to NOSQL Databases. In: Kaiser, M.S., Xie, J., Rathore, V.S. (eds) Intelligent Strategies for ICT. ICTCS 2023. Lecture Notes in Networks and Systems, vol 941. Springer, Singapore. https://doi.org/10.1007/978-981-97-1260-1_12
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