Efficiency of JSON approach for Data Extraction and Query Retrieval

2016 ◽  
Vol 4 (1) ◽  
pp. 203 ◽  
Author(s):  
Mohd Kamir Yusof ◽  
Mustafa Man
Keyword(s):  
Information System ◽  
Relational Database ◽  
Execution Time ◽  
Database Management ◽  
Data Extraction ◽  
Extensible Markup Language ◽  
Markup Language ◽  
Huge Data ◽  
Extensible Markup ◽  
Database Technology

<p>Students’ Information System (SIS) in Universiti Sultan Zainal Abidin (UniSZA) handles thousands of records on the information of students, subject registration, etc. Efficiency of storage and query retrieval of these records is the matter of database management especially involving with huge data. However, the execution time for storing and retrieving these data are still considerably inefficient due to several factors. In this contribution, two database approaches namely Extensible Markup Language (XML) and JavaScript Object Notation (JSON) were investigated to evaluate their suitability for handling thousands records in SIS. The results showed JSON is the best choice for storage and query speed. These are essential to cope with the characteristics of students’ data. Whilst, XML and JSON technologies are relatively new to date in comparison to the relational database. Indeed, JSON technology demonstrates greater potential to become a key database technology for handling huge data due to an increase of data annually.</p>

Efficiency of JSON for Data Retrieval in Big Data

2017 ◽  
Vol 7 (1) ◽  
pp. 250
Author(s):  
Mohd Kamir Yusof
Keyword(s):  
Big Data ◽  
Large Volume ◽  
Data Retrieval ◽  
Markup Language ◽  
Publication Data ◽  
Huge Data ◽  
Powerful Approach ◽  
Extensible Markup ◽  
Database Technology ◽  
And Storage

Big data is the latest industry buzzword to describe large volume of structured and unstructured data that can be difficult to process and analyze. Most of organization looking for the best approach to manage and analyze the large volume of data especially in making a decision. XML is chosen by many organization because of powerful approach during retrieval and storage processes. However, XML approach, the execution time for retrieving large volume of data are still considerably inefficient due to several factors. In this contribution, two databases approaches namely Extensible Markup Language (XML) and Java Object Notation (JSON) were investigated to evaluate their suitability for handling thousands records of publication data. The results showed JSON is the best choice for query retrieving speed and CPU usage. These are essential to cope with the characteristics of publication’s data. Whilst, XML and JSON technologies are relatively new to date in comparison to the relational database. Indeed, JSON technology demonstrates greater potential to become a key database technology for handling huge data due to increase of data annually.

scholarly journals Storing XML Documents in Databases

2005 ◽  
pp. 658-664
Author(s):  
Albrecht Schmidt ◽  
Stefan Manegold ◽  
Martin Kersten
Keyword(s):  
Data Management ◽  
Relational Database ◽  
Query Language ◽  
Transaction Management ◽  
Markup Language ◽  
Xml Documents ◽  
Management Technology ◽  
Extensible Markup ◽  
Database Technology ◽  
Exchange Data

Ever since the Extensible Markup Language (XML) (W3C, 1998b) began to be used to exchange data between diverse sources, interest has grown in deploying data management technology to store and query XML documents. A number of approaches propose to adapt relational database technology to store and maintain XML documents (Deutsch, Fernandez & Suciu, 1999; Florescu & Kossmann, 1999; Klettke & Meyer, 2000; Shanmugasundaram et al., 1999; Tatarinov et al., 2002; O’Neil et al., 2004). The advantage is that the XML repository inherits all the power of mature relational technology like indexes and transaction management. For XML-enabled querying, a declarative query language (Chamberlin et al., 2001) is available.

scholarly journals Efficiency of Flat File Database Approach in Data Storage and Data Extraction for Big Data

2018 ◽  
Vol 9 (2) ◽  
pp. 460
Author(s):  
Mohd Kamir Yusof ◽  
Mustafa Man
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Large Volume ◽  
Data Extraction ◽  
Flat File ◽  
Huge Data ◽  
Powerful Approach ◽  
Extensible Markup ◽  
Database Technology ◽  
And Storage

Big data is the latest industry buzzword to describe large volume of structured and unstructured data that can be difficult to process and analyze. Most of organization looking for the best approach to manage and analyze the large volume of data especially in making a decision. XML and JSON are chosen by many organization because of powerful approach during retrieval and storage processes. However, these approaches, the execution time for retrieving large volume of data are still considerably inefficient due to several factors. In this contribution, three databases approaches namely Extensible Markup Language (XML), Java Object Notation (JSON) and Flat File database approach were investigated to evaluate their suitability for handling thousands records of publication data. The results showed flat file is the best choice for query retrieving speed and CPU usage. These are essential to cope with the characteristics of publication’s data. Whilst, XML, JSON and Flat File database approach technologies are relatively new to date in comparison to the relational database. Indeed, Text File Format technology demonstrates greater potential to become a key database technology for handling huge data due to increase of data annually.

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