The amount of data available in XML is rapidly increasing and at the same time the price of mass storage is rapidly decreasing, and this makes it possible to store larger amounts of data. The contents of a database or data warehouse are seldom static. New documents are created, documents are deleted and, more important, documents are updated. In many cases, one wants to be able to search in historical (old) versions, retrieve documents that were valid at a certain time, query changes to documents, and so forth. (Note that although this process is somewhat similar to general document versioning maintenance, the aspect of time makes possibilities and appropriate solutions different.) The “easiest” way to do this is to store all versions of all documents in the database and use a middleware layer to convert temporal query language statements into conventional statements, executed by an underlying database system (an example of such a system is TeXOR; Nørvåg, Limstrand, & Myklebust, 2003). Although this approach makes the introduction of temporal support easier, it can be difficult to achieve good performance: temporal query processing is in general costly, and the cost of storing the complete document versions can be high. Thus, a temporal XML database system is necessary.
Concurrent query processing in a GPU-based database system
