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Reseach Article

Database Migration from Structured Database to non-Structured Database

Published on May 2015 by Mital Potey, Megha Digrase, Gaurav Deshmukh, Minal Nerkar
International Conference on Recent Trends & Advancements in Engineering Technology
Foundation of Computer Science USA
ICRTAET2015 - Number 1
May 2015
Authors: Mital Potey, Megha Digrase, Gaurav Deshmukh, Minal Nerkar
f304e886-9ac4-47b4-ae32-dae0fd5bedf7

Mital Potey, Megha Digrase, Gaurav Deshmukh, Minal Nerkar . Database Migration from Structured Database to non-Structured Database. International Conference on Recent Trends & Advancements in Engineering Technology. ICRTAET2015, 1 (May 2015), 1-3.

@article{
author = { Mital Potey, Megha Digrase, Gaurav Deshmukh, Minal Nerkar },
title = { Database Migration from Structured Database to non-Structured Database },
journal = { International Conference on Recent Trends & Advancements in Engineering Technology },
issue_date = { May 2015 },
volume = { ICRTAET2015 },
number = { 1 },
month = { May },
year = { 2015 },
issn = 0975-8887,
pages = { 1-3 },
numpages = 3,
url = { /proceedings/icrtaet2015/number1/20942-1710/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Trends & Advancements in Engineering Technology
%A Mital Potey
%A Megha Digrase
%A Gaurav Deshmukh
%A Minal Nerkar
%T Database Migration from Structured Database to non-Structured Database
%J International Conference on Recent Trends & Advancements in Engineering Technology
%@ 0975-8887
%V ICRTAET2015
%N 1
%P 1-3
%D 2015
%I International Journal of Computer Applications
Abstract

Database are growing very fast and becoming more complex in the volume (terabyte to petabyte), variety (structured, un-structured and hybrid), and velocity (high speed in growth). Management of database (BigData, so nomenclature) has become the global challenge. The data collection is currently managed and exploited mostly by using conventional data management tools such as classic relational database management systems (RDBMS) or conventional search engines. These systems and tools have been observed to be inefficient and incapable to handle the data in most of the cases e. g. : social networking sites. Efforts are being made to come up with some utility support in order to overcome the observed limitations. The research study was conducted to develop a Cloud-based Utility. It was aimed to convert structural database, SQL to un-structural database, NoSQL [11] systematically and sufficiently. The outcome of the study revealed that the database management becomes considerably scalable, flexible and efficient when traditional RDBMS are complimented by specifically designed rich set of alternative DBMS such as NoSQL, NewSQL based systems. The database conversion shall help in Database analysis and migration from traditional database to today's BigData.

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Index Terms

Computer Science
Information Sciences

Keywords

Sql Nosql Database Python Django Bigdata.