Michael M David

This two-part article will change your view and understanding of standard SQL and its ability to integrate naturally and fully with native XML. The perceived problem with achieving full SQL-based integration of XML is that relational data is flat while XML data is hierarchical, producing a huge impediment to a seamless solution. This belief has prevented a full integration solution, resulting in SQL vendors resorting to nonstandard SQL and external code, whose solutions fall far short of full XML integration. The usual method of integration used by SQL vendors is to shred or flatten the XML data in order to join it relationally with the relational data. This produces major efficiency problems for processing and memory utilization and ignores the hierarchical semantics in the XML data, which can be valuable. This article demonstrates how standard ANSI SQL-92 can perf... (more)

Advanced ANSI SQL Native XML Integration-Part 2 - Supporting advanced XML capabilities

Part 1 of this article demonstrated how standard ANSI SQL can integrate fully, naturally, and seamlessly with XML. This was accomplished by naturally raising SQL processing to a hierarchical level, enabling relational data (including XML-shredded data) to integrate at a full hierarchical level with native XML. Hierarchical processing and the utilization of the hierarchical semantics were also shown in Part 1, along with the hierarchical joining of hierarchical structures. Part 2 will cover how standard SQL can naturally support more advanced XML capabilities such as node promoti... (more)

SQL Transparent Hierarchical Processing of Relational, XML and IMS Data

Current SQL support of relational, XML and hierarchical legacy data such as IMS is driven by flattening the hierarchical data in order to integrate it naturally with relational (flat) data so that it can be processed relationally. Unfortunately, this strips out the natural semantics in hierarchical data which has the capability to dynamically increase the value of the data being processed and to perform powerful hierarchical operations. The SQL-92 standard introduced the LEFT Outer Join which offers a powerful alternative to standard relational processing that can be used to perfo... (more)

Naturally Increasing Data Value with Hierarchical Structures

Hierarchical structures have an inherent ability for significant data value increases beyond the data collected.  This will be shown to exist in hierarchical structures and even more powerfully in their natural hierarchical processing capabilities. These will demonstrate flexible and efficient ways to increase data value automatically and will be discussed in this article. SQL will be used to perform a wide range of hierarchical processing operations that easily demonstrate these increasing data value capabilities. Basic Hierarchical Data Modeling The SQL view definition in Figu... (more)

SQL Peer-to-Peer Dynamic Structured Data Processing Collaboration

Unstructured and XML semi-structured data is now used more than structured data. Unstructured data is useful because of its fuzzy processing applied to this more common ubiquitous data.  But fixed structured data still keeps businesses running day in and day out, which requires consistent predictable highly principled processing for correct results. This means structured data cannot be replaced by unstructured or semi-structured data.  For this reason, it would be very useful to have a general purpose peer-to-peer collaboration capability that can utilize highly principled hierar... (more)