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XML Databases
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With the proliferation of XML usage and XML documents, several venture-backed startup companies have been formed to commercialize native XML databases. Typically, these databases store and model their data contents as XML documents. The actual database contents may be stored in native form as XML text, or in some parsed form such as that maintained by a DOM XML parser. Most of the XML database products currently support XPath as a core query capability, and many of them have added proprietary extensions to XPath to make it a more complete query language. They typically pledge support for XQuery as a replacement for XPath or as a second, complementary query language, as soon as the XQuery specification is finalized. The vendors of native XML databases tend to make the same arguments in favor of their products that the object-oriented database vendors made a decade earlier. With external data increasingly represented as XML, the best match is a database that carries the same underlying data model. The choice of XML documents as a native format reduces the overhead of XML marshaling and unmarshaling, but provides the same level of individual element and attribute access and navigation. Finally, they say that with a growing body of users trained in HTML and XML, an XML database can be more accessible to more people than SQL-based relational databases. It is still too soon to judge the eventual market success and impact of the native XML databases. It seems likely that a native XML database may be a good match for data management needs within an XML-based web site for storing, accessing, and transforming XML documents. However, the previous history of pure object-oriented databases suggests that relational database vendors are capable of extending their core products to incorporate the most important features of new data models at a pace that is fast enough to retain their dominant market shares. It seems very likely that relational databases will remain the dominant native database type for data processing applications. But within these products, XML integration will grow tighter over time, and relational products will offer more and more XML-oriented features.
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25:
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Summary
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This chapter described the relationships between XML and SQL, and between XML documents and relational databases: XML has its origins in printing and publishing; it was originally designed as a way to indicate and specify document contents. XML s document orientation produces a natural hierarchical view of data. The mismatch between XML hierarchies and SQL row/column tables is one of the biggest challenges when integrating the two technologies. XML documents comprise a hierarchy of elements. Elements can carry contents, they can have named attributes, and they can have other elements as children. XML integration with relational databases can take several forms, including XML query output, XML input, XML data exchange, and the storage and retrieval of XML data within the database itself. XML Schema, and an older standard, XML DTDs, define rigid structures for specific types of documents. They are useful to restrict document contents to a standard form acceptable for data processing applications. XQuery is an emerging query language for XML documents. It has some parallels to SQL, but its focus on expressions and path navigation make it quite different in style from SQL. Native XML databases have been introduced and are moving to adopt XQuery as a native query language. They pose a challenge to the relational model, but major DBMS vendors are moving quickly to provide XML extensions to their relational products.
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PART VI
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CHAPTER
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Specialty Databases
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oday s database market is dominated by the major enterprise database management systems. The flagship products from Oracle, IBM, Microsoft, Sybase, and others are large, complex pieces of software that have evolved to a one size fits all approach. Large companies can use the latest version of the Oracle database or of IBM s DB2 to process online transactions from their web site, to store data warehouses and analyze business data, to manage data for their accounting and finance systems, and to support departmental database use. These applications represent different workloads, but the enterprise database products are broad enough and flexible enough to address them all. Some database applications, however, have requirements that are so specialized or so stringent that the mainstream enterprise databases cannot stretch far enough to address them effectively. These applications remain the domain of specialty or niche database products. It s a testimony to the power of SQL that even these specialized, niche database products are SQL-based today. This chapter examines four of these database niches, the specialty databases that address them, and the SQL features that have been added to meet their requirements.
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