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

Abstract

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.

Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying

“…We describe two approaches for i) offline context-based XML document disambiguation and ii) online global keyword query disambiguation, both designed to run in almost linear time. Our solution is: i) fully automated, compared with existing interactive solutions which require user input to manually identify the intended query senses e.g., [35,61], and ii) tractable (of almost linear time) and thus reasonably applicable on the Web, compared with polynomial or exponential solutions, e.g., [23,58]. Our solution also provides iii) a dedicated index structure to handle semantic XML trees, iv) a dedicated query formalism to allow structure-and-content queries with only partial knowledge of the data collection structure and semantics, and iv) three alternative query processing algorithms to evaluate query processing time and quality.…”

“…Nonetheless, time complexity is critical for on-the-fly execution on the Web (in comparison with document semantic analysis which could be performed offline). The time complexity of query semantic analysis might even prove to be problematic in the case of the pattern recognition-based methods [19,54], since traditional structure pattern recognition problems are usually of exponential complexity [25,58].…”

An Efficient Prefix-Based Labeling Scheme for XML Dynamic Updates Using Hexagonal Pattern

“…Indeed, XML has attracted broad acceptance and support from all of the major providers of databases, servers, and software tools [4,5]. XML is a hierarchical, self-describing semi-structured data format that employs an easy-to-write and easy-to-parse syntax to simplify data interchange across a variety of Web-based applications [5][6][7]. It provides communication across multiple computing systems, which was previously extremely difficult, if not impossible.…”

“…However, XML is used to represent a large amount of semi-structured data on the Internet. As a result, handling these data in terms of storage, updating, and querying has become a big challenge [2,[7][8][9][10].…”

“…This improves XML data storage, updates, and queries. [7,17,18]. The adoption of a labeling scheme improves the efficiency of XML data retrieval and indexing because its usage results in a reduction in the query processing time [19,20].…”