XML database

Reasons to store data in XML format as an XML database include:{{cite web|last1=Nicola|first1=Matthias|title=5 Reasons for Storing XML in a Database|url=http://nativexmldatabase.com/2010/09/28/5-reasons-for-storing-xml-in-a-database/|website=Native XML Database|access-date=17 March 2015|date=28 September 2010}}

{{cite conference|last1=Feldman|first1=Damon|title=Moving from Relational Modeling to XML and MarkLogic Data Models|url=http://www.marklogic.com/resources/slides-moving-from-relational-modeling-to-xml-and-marklogic-data-models/resource_download/presentations/|conference=MarkLogic World|conference-url=http://world.marklogic.com/|date=11 April 2013|access-date=17 March 2015}}

• An enterprise may have numerous XML documents with similar data, but dispersed in different XML formats. Conglomerating this data into a singular, standardized XML database structure will avoid compatibility issues
• Data may need to be exposed or ingested as XML, so using another format such as relational forces double-modeling of the data
• XML is very well suited to parse data, deeply nested data and mixed content (such as text with embedded markup tags)
• XML is human readable whereas relational tables require expertise to access
• Metadata is often available as XML
• Semantic web data is available as RDF/XML
• Provides a solution for Object-relational impedance mismatch[NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence. Addison-Wesley Educational Publishers Inc, 2009] {{ISBN|978-0321826626}}

Steve O'Connell gives one reason for the use of XML in databases: the increasingly common use of XML for data transport, which has meant that "data is extracted from databases and put into XML documents and vice-versa".{{cite report|author=O'Connell, Steve|work=Advanced Databases Course Notes|title=Section 9.2|type=Syllabus|date=2005|publisher=University of Southampton|location=Southampton, England}}{{update inline|date=March 2015}} It may prove more efficient in terms of conversion costs,{{Citation needed|date=December 2024}} and easier to store the data in XML format. In content-based applications, the ability of the native XML database also minimizes the need for extraction or entry of metadata to support searching and navigation.

XML-enabled databases typically offer one or more of the following approaches to storing XML within the traditional relational structure:

1. XML is stored into a CLOB (Character large object)
2. XML is `shredded` into a series of Tables based on a Schema{{cite book|title=Oracle XML DB Developer's Guide, 10g Release 2|date=August 2005|publisher=Oracle Corporation|chapter-url=http://docs.oracle.com/cd/B19306_01/appdev.102/b14259/xdb05sto.htm|access-date=17 March 2015|chapter=XML Schema Storage and Query: Basic}}. Section [http://docs.oracle.com/cd/B19306_01/appdev.102/b14259/xdb05sto.htm#i1042421 Creating XMLType Tables and Columns Based on XML Schema]
3. XML is stored into a native XML Type as defined by ISO Standard 9075-14{{cite web|title=ISO/IEC 9075-14:2011: Information technology -- Database languages -- SQL -- Part 14: XML-Related Specifications (SQL/XML)|url=http://www.iso.org/iso/home/store/catalogue_ics/catalogue_detail_ics.htm?csnumber=53686|publisher=International Organization for Standardization|access-date=17 March 2015|date=2011}}

RDBMS that support the ISO XML Type are:

1. IBM DB2 (pureXML{{cite web|title=pureXML overview -- DB2 as an XML database|url=http://www-01.ibm.com/support/knowledgecenter/SSEPGG_10.1.0/com.ibm.db2.luw.xml.doc/doc/c0022308.html|website=IBM Knowledge Center|publisher=IBM|access-date=17 March 2015}})
2. Microsoft SQL Server{{cite web|title=Using XML in SQL Server|url=https://msdn.microsoft.com/en-us/library/ms190936.aspx|website=Microsoft Developer Network|publisher=Microsoft Corporation|access-date=17 March 2015}}
3. Oracle Database{{cite book|title=Oracle XML DB Developer's Guide, 10g Release 2|date=August 2005|publisher=Oracle Corporation|chapter-url=http://docs.oracle.com/cd/B19306_01/appdev.102/b14259/xdb04cre.htm|access-date=17 March 2015|chapter=XMLType Operations}}
4. PostgreSQL{{cite book|title=PostgreSQL 9.6 Documentation|chapter-url=https://www.postgresql.org/docs/9.6/static/datatype-xml.html|access-date=1 April 2017|chapter=8.13. XML Type}}

Typically an XML-enabled database is best suited where the majority of data are non-XML. For datasets where the majority of data are XML, a native XML database is better suited.

select

id, vol, xmlquery('$j/name', passing journal as "j") as name

from

journals

where

xmlexists('$j[licence="CreativeCommons"]', passing journal as "j")

XML databases are often used in combination with relational databases to manage and store hierarchical data. A significant challenge in such integrations is extracting XML documents from relational databases, which requires specialized techniques and tools. These techniques often include:

1. Mapping Relational Data to XML: Schema mapping is a critical process that defines how relational tables correspond to XML elements and attributes.
2. XQuery Processing: Querying XML data extracted from relational databases may involve XQuery, a language designed for querying and transforming XML.

One of the most common scenario involves converting relational data into XML documents{{Cite web |date=2025-01-01 |title=Extracting XML Documents from Relational Databases - 7 Tips |url=https://vividorigins.com/xml-documents-from-relational-databases/ |access-date=2025-01-06 |website=Vivid Origins |language=en-US}} to facilitate standards with systems relying on XML-based standards, such as web services or APIs. This process is important in applications where structured and semi-structured data co-exist and must be integrated perfectly.

For example, extracting hierarchical data from relational databases and converting it into XML is a common approach when generating XML feeds, exchanging data between systems, or implementing XML-based configurations.

Native XML databases are especially tailored for working with XML data. As managing XML as large strings would be inefficient, and due to the hierarchical nature of XML, custom optimized data structures are used for storage and querying. This usually increases performance both in terms of read-only queries and updates.{{cite web|last1=Matthias|first1=Nicola|title=XML versus Relational Database Performance|url=https://nativexmldatabase.com/2010/08/22/xml-versus-relational-database-performance/|website=Native XML Database|access-date=28 Jun 2017|date=22 August 2010}} XML nodes and documents are the fundamental unit of (logical) storage, just as a relational database has fields and rows.

The standard for querying XML data per W3C recommendation is XQuery; the latest version is XQuery 3.1.{{cite web|url=http://www.w3.org/TR/xquery-31/ | title=XQuery 3.1 Recommendation | date=2017-03-21}} XQuery includes XPath as a sub-language and XML itself is a valid sub-syntax of XQuery. In addition to XPath, some XML databases support XSLT as a method of transforming documents or query results retrieved from the database.

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For data-centric XML datasets, the unique and distinct keyword search method, namely, XDMA{{Cite journal|last1=Selvaganesan|first1=S.|last2=Haw|first2=Su-Cheng|last3=Soon|first3=Lay-Ki|title=XDMA: A Dual Indexing and Mutual Summation Based Keyword Search Algorithm for XML Databases|journal=International Journal of Software Engineering and Knowledge Engineering|language=en-US|volume=24|issue=4|pages=591–615|doi=10.1142/s0218194014500223|year=2014}} for XML databases is designed and developed based on dual indexing and mutual summation.

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Category:XML

Category:Data management

Category:Data modeling

Category:Database management systems