Graph-Based Denormalization for Migrating Big Data from SQL Database to NoSQL Database

被引：0
作者：
Rathika, V [1 ]
机构：
[1] Mother Teresa Womens Univ, Dept Comp Sci, Kodaikanal, Tamil Nadu, India
来源：
INTELLIGENT COMMUNICATION TECHNOLOGIES AND VIRTUAL MOBILE NETWORKS, ICICV 2019 | 2020年 / 33卷
关键词：
Big data; Data migration; Denormalization; Map Reduce; NoSQL database;
D O I：
10.1007/978-3-030-28364-3_56
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this big data era, the data storing methods are vary based upon the data type and the technologies upgradation. Due to the increase of voluminous data, the traditional Relational Database Management Systems (RDBMS) are immature to handle the unstructured data. To overcome this issue, NoSQL databases are used to store and process the unstructured data. The big data migration from SQL to NoSQL database is more complex. The SQL databases are well-normalized database. Denormalization plays a major role in retrieving the data more efficiently. This work is carried on migrating the big data from SQL to NoSQL database using the Graph-based Denormalization method. The proposed method is more efficient for big data migration and post-migration process.
引用
收藏
页码：546 / 556
页数：11
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