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.

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>

XRecursive

2011 ◽  
Vol 1 (4) ◽  
pp. 53-65 ◽  
Author(s):  
Mohammed Adam Ibrahim Fakharaldien ◽  
Jasni Mohamed Zain ◽  
Norrozila Sulaiman ◽  
Tutut Herawan
Keyword(s):  
Relational Database ◽  
Relational Databases ◽  
Structured Data ◽  
Markup Language ◽  
Xml Data ◽  
Xml Documents ◽  
Extra Effort ◽  
Extensible Markup ◽  
Promising Solution ◽  
Reconstruction Time

Storing XML documents in a relational database is a promising solution because relational databases are mature and scale very well. They have the advantages that in a relational database XML data and structured data can coexist making it possible to build application that involve both kinds of data with little extra effort. This paper proposes an alternative method named Xrecursive for mapping XML (eXtensible Markup Language) documents to RDB (Relational Databases). The Xrecursive method does not need a DTD (Document Text Definition) or XML schema. Further, it can be applied as a general solution for any XML data. The steps and algorithm of Xrecursive are given in details to describe how to use the storing structure to storage and query XML documents in relational database. The authors report their experimental results on a real database, showing that the performance of their Xrecursive algorithm achieves better results in terms of storage size, insertion time, mapping time, and reconstruction time as compared with that SUCXENT and XParent methods. In overall, Xrecursive performs better in term of query performances as compared to the both methods.

FUZZY DATA REPRESENTATION AND QUERYING IN XML DATABASE

2007 ◽  
Vol 15 (supp01) ◽  
pp. 43-57 ◽  
Author(s):  
EKİN ÜSTÜNKAYA ◽  
ADNAN YAZICI ◽  
ROY GEORGE
Keyword(s):  
Query Language ◽  
Data Representation ◽  
Xml Schema ◽  
Fuzzy Data ◽  
Markup Language ◽  
Imprecise Data ◽  
Xml Documents ◽  
Extensible Markup ◽  
World Information ◽  
Application Specific

Real-world information including subjective opinions and judgments need imprecise data to be modeled for representation and querying in databases. The Extensible Markup Language (XML) has become a de-facto standard for data modeling and exchange in recent years. Efforts on modeling imprecision and representing such data in XML have not been fully developed. In this paper, an XML based fuzzy data representation and querying system is presented. Complex and imprecise data are represented using a fuzzy extension of XML. The representation forms the basis for a system which enables fuzzy querying on XML documents using XQuery, a XML query language. The system also enables restructuring of XML Schemas through merging of elements of the XML documents. By using this feature of the system, application specific XML Schema and XML documents can be generated from the existing documents.

An Algorithm for Transforming XML Documents Schema into Relational Database Schema

2011 ◽  
pp. 171-189 ◽  
Author(s):  
Abad Shah ◽  
Jacob Adeniyi ◽  
Tariq Al Tuwairqi
Keyword(s):  
Relational Database ◽  
Database Schema ◽  
The Internet ◽  
Xml Documents ◽  
Simpler Algorithm ◽  
Xml Document ◽  
Database Technology ◽  
Relational Database Schema ◽  
Xml Technologies ◽  
The Web

The Web and XML have influenced all walks of lives of those who transact business over the Internet. People like to do their transactions from their homes to save time and money. For example, customers like to pay their utility bills and other banking transactions from their homes through the Internet. Most companies, including banks, maintain their records using relational database technology. But the traditional relational database technology is unable to provide all these new facilities to the customers. To make the traditional relational database technology cope with the Web and XML technologies, we need a transformation between the XML technology and the relational database technology as middleware. In this chapter, we present a new and simpler algorithm for this purpose. This algorithm transforms a schema of a XML document into a relational database schema, taking into consideration the requirement of relational database technology.

Abstract DTD Graph from an XML Document

2010 ◽  
pp. 204-224
Author(s):  
Joseph Fong ◽  
Herbert Shiu
Keyword(s):  
Relational Database ◽  
The Internet ◽  
Conceptual Schema ◽  
Reverse Engineer ◽  
Xml Documents ◽  
Data Interchange ◽  
Data Semantics ◽  
Xml Document ◽  
Extensible Markup ◽  
Implicit And Explicit

Extensible Markup Language (XML) has become a standard for persistent storage and data interchange via the Internet due to its openness, self-descriptiveness and flexibility. This chapter proposes a systematic approach to reverse engineer arbitrary XML documents to their conceptual schema – Extended DTD Graphs ? which is a DTD Graph with data semantics. The proposed approach not only determines the structure of the XML document, but also derives candidate data semantics from the XML element instances by treating each XML element instance as a record in a table of a relational database. One application of the determined data semantics is to verify the linkages among elements. Implicit and explicit referential linkages are among XML elements modeled by the parent-children structure and ID/IDREF(S) respectively. As a result, an arbitrary XML document can be reverse engineered into its conceptual schema in an Extended DTD Graph format.

A Narrative Review of Storing and Querying XML Documents Using Relational Database

2019 ◽  
Vol 18 (04) ◽  
pp. 1950048
Author(s):  
Amjad Qtaish ◽  
Mohammad T. Alshammari
Keyword(s):  
Relational Database ◽  
File Systems ◽  
Data Representation ◽  
Xml Data ◽  
Xml Documents ◽  
Data Interchange ◽  
Extensible Markup ◽  
Data Environment ◽  
Object Oriented Database ◽  
The Web

Extensible Markup Language (XML) has become a common language for data interchange and data representation in the Web. The evolution of the big data environment and the large volume of data which is being represented by XML on the Web increase the challenges in effectively managing such data in terms of storing and querying. Numerous solutions have been introduced to store and query XML data, including the file systems, Object-Oriented Database (OODB), Native XML Database (NXD), and Relational Database (RDB). Previous research attempts indicate that RDB is the most powerful technology for managing XML data to date. Because of the structure variations of XML and RDB, the need to map XML data to an RDB scheme is increased. This growth has prompted numerous researchers and database vendors to propose different approaches to map XML documents to an RDB, translating different types of XPath queries to SQL queries and returning the results to an XML format. This paper aims to comprehensively review most cited and latest mapping approaches and database vendors that use RDB solution to store and query XML documents, in a narrative manner. The advantages and the drawbacks of each approach is discussed, particularly in terms of storing and querying. The paper also provides some insight into managing XML documents using RDB solution in terms of storing and querying and contributes to the XML community.

On an Enhancement of XML Applied for Mobile E-Commerce

2012 ◽  
Vol 10 (3) ◽  
pp. 13-26
Author(s):  
Xiaomin Zhu ◽  
Zhongxiang He ◽  
Shengbo Shi
Keyword(s):  
Data Processing ◽  
Mobile Computing ◽  
Web Service ◽  
Size Effects ◽  
Processing Time ◽  
The Internet ◽  
Markup Language ◽  
Mobile Web ◽  
Xml Documents ◽  
Extensible Markup

Extensible Markup Language (XML) is a textual markup language which becomes more and more important in the Internet web service. However, some distinct disadvantages exist in XML, such as its nature of redundancy, which consumes the limited network’s bandwidth greatly especially in mobile computing. Considering the characteristics of the mobile commerce, the handsets’ memory capability and data processing time are two problems for XML being applied. This paper studies an enhancement of XML for the purpose of application in mobile e-commerce, called SXML, which means Simple XML to enhance the XML used in mobile web service. It helps XML producers minimizing the size effects of XML, e.g., the size overhead and slow implementation speed. Comprehensive simulations show that the SXML could reduce the size of XML documents and reduce the time of implementation, consequently utilize the bandwidth effectively.

Mining Association Rules from XML Documents

2011 ◽  
pp. 879-899
Author(s):  
Laura Irina Rusu ◽  
Wenny Rahayu ◽  
David Taniar
Keyword(s):  
Knowledge Discovery ◽  
Association Rules ◽  
Web Application ◽  
Semistructured Data ◽  
Markup Language ◽  
Xml Documents ◽  
Rapid Changes ◽  
Extensible Markup ◽  
Hidden Knowledge ◽  
The Web

This chapter presents some of the existing mining techniques for extracting association rules out of XML documents in the context of rapid changes in the Web knowledge discovery area. The initiative of this study was driven by the fast emergence of XML (eXtensible Markup Language) as a standard language for representing semistructured data and as a new standard of exchanging information between different applications. The data exchanged as XML documents become richer and richer every day, so the necessity to not only store these large volumes of XML data for later use, but to mine them as well to discover interesting information has became obvious. The hidden knowledge can be used in various ways, for example, to decide on a business issue or to make predictions about future e-customer behaviour in a Web application. One type of knowledge that can be discovered in a collection of XML documents relates to association rules between parts of the document, and this chapter presents some of the top techniques for extracting them.

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.

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