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Data transformation methodologies between heterogeneous data stores: A comparative study

: Chakrabarti, Arnab; Jayapal, Manasi


Bernardino, J. ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
DATA 2017, 6th International Conference on Data Science, Technology and Applications. Proceedings : Madrid, Spain, July 24-26, 2017
SciTePress, 2017
ISBN: 978-989-758-255-4
International Conference on Data Science, Technology and Applications (DATA) <6, 2017, Madrid>
Conference Paper
Fraunhofer FIT ()

With the advent of the NoSQL Data Stores, solutions for data migration from traditional relational databases to NoSQL databases is gaining more impetus in the recent times. This is also due to the fact that data generated in recent times are more heterogeneous in nature. In current available literatures and surveys we find that in-depth study has been already conducted for the tools and platform used in handling structured, unstructured and semi-structured data, however there are no guide which compares the methodologies of transforming and transferring data between these data stores. In this paper we present an extensive comparative study where we compare and evaluate data transformation methodologies between varied data sources as well as discuss the challenges and opportunities associated with it.