Currently available DBMSs provide little support for queries over ordered collection of records, or sequences, and over temporal data. Typical sequence queries include "Find the weekly moving average of the Dow Jones Industrial Average," and "Find the first five consecutively increasing temperature readings" (from a trace of temperature observations). Such queries can be easily expressed and often effciently executed by systems that support query languages designed for sequences. Some commercial SQL systems now support such SQL extensions.
The first example is also a temporal query. However, temporal queries involve more than just record ordering. For example, consider the following query: Find the longes interval in which the same person managed two different departments." If the period during which a given person managed a department is indicated by two fields from and to, we have to reason about a collection of intervals, rather than a sequence of records.
Further, temporal queries require the DBMS to be aware of the anomalies associated with calendars (such as leap years). Temporal extensions are likely to be incorporated in future versions of the SQL standard.
A distinct and important class of sequence data consists of DNA sequences, which are being generated at a rapid pace by the biological community. These are in fact closer to sequences of characters in text than to time sequences as in the above examples. The field of biological information management and analysis has become very popular in recent years, and is called bioinformatics. Biological data, such as DNA sequence data, is characterized by complex structure and numerous relationships among data elements, many overlapping and incomplete or erroneous data fragments (because experimentally collected data from several groups, often working on related problems is stored in the databases), a need to frequently change the database schema itself as new kinds of relationships in the data are discovered, and the need to maintain several versions of data for archival and reference.