XML Data Store Multi-Client Study

While much has been written about XML data storage, none of the research to date has focused on the key questions:

• What are the different needs for XML data storage?
• ow do those needs translate into different storage requirements?
• How are various vendor solutions best suited to meet these different needs?

In attempting to understand the answers to the above questions, ZapThink realized that there was no single answer for any of these key questions. In fact, it seems that the various requirements for XML data storage pull end-user customers in different directions when they are deciding how to implement XML storage requirements. As such, this study seeks to do what no other study before it has done: show that XML data storage is not a distinct market segment, but instead a functionality requirement for applications that require XML storage in order to achieve their overall system objectives.

ZapNote: B-Bop

The only true solutions for enterprise-wide XML data storage and retrieval are XML-enabled RDBMS and Native XML Data Store (NXD) approaches. The challenge with XML-enabled RDBMS is that they are not very well suited to highly extensible and flexible documents, while the challenge with NXDs is that they are unproven technologies with very small user bases. However, there is another option that is a sort of "middle ground": the use of an interpretive middle layer over standard RDBMS systems that offers schema-independent, "native" XML data storage. In this vein, B-Bop offers their Xfinity Server as a way of providing the features of Native XML storage while utilizing existing relational storage architectures.

XML Data Storage Technologies & Trends

While file systems, relational, and object-oriented database management systems have met our needs in prior years for data storage and retrieval, XML imposes new requirements on how that information needs to be stored so that it can be retrieved in a structured, hierarchical manner. This ZapThink report, “XML Data Storage Technologies and Trends” covers the various commercial options that focus on meeting the requirements for XML storage and retrieval, and identifies benefits, disadvantages, key market drivers, and sizing and growth of the market for these products.

XML Data Storage Technologies and Trends

While file systems, relational, and object-oriented database management systems have met our needs in prior years for data storage and retrieval, XML imposes new requirements on how that information needs to be stored so that it can be retrieved in a structured, hierarchical manner. This ZapThink report, “XML Data Storage Technologies and Trends” covers the various commercial options that focus on meeting the requirements for XML storage and retrieval, and identifies benefits, disadvantages, key market drivers, and sizing and growth of the market for these products.

ZapNote: eXcelon

There are two major categories of XML data store: extensions to relational database systems (RDBMS) and a new category of "Native" XML data stores (NXDs). While extensions to RDBMS systems simply enable RDBMS databases to map XML documents to relational tables, NXDs allow users to insert XML documents directly into the system without need for mapping or interacting with anything besides the XML document. eXcelon’s eXtensible Information Server (XIS) is an "XML data management system (XDBMS)" that is aimed squarely at the problem of storing arbitrarily structured XML documents. Among other features, XIS provides node level management of XML data, dealing with XML document information at the element level, rather than the document level.

ZapNote: XYZFind

XYZFind provides a general-purpose NXD storage and retrieval system for XML documents, regardless of their content or schema. XYZFind aims to solve the problem of search and query over identifiable "islands of data" where the content its too varied to accommodate with file system tools. XYZFind’s utilizes a proprietary query language and has a proprietary, text-based storage architecture that utilizes a meta-schema encompassing an aggregate, schema-independent view of the data.