Comparison Of Temporal Query Approaches Between Data Warehouses And Temporal Databases

Along with the popularizing and spreading of computers, DBMSs have become essential components of daily living for human being. Many enterprises have stored lots of worth data since their systems run. The development of DBMSs is nowadays tending to effectively, synthetically and systematically organize and utilize the data; effectively mine the rules from the data, which can be used to guide the enterprise to operate in the future. It is data warehouses that become one of the solutions for above issues. On the other hand, time information is getting more and more important in applications now. How to handle this information is also being another hot topic in Database field. The relationship between DW and TDB is very intimate. As a rollback database case, DW is constituted of a series of snapshot databases, belonging to one kind of TDBs. DW is very powerful; its analytic tools are mainly OLAP and Data Mining. Although they are independent relatively, the both tools are closely related. In practice, we should combine and coordinate them to make the most of these tools. In this paper, data warehouses are compared with temporal databases on temporal query. It follows that DWs are defective on temporal query and it is purposed to add the temporal technique into DWs to strengthen their functions of temporal query. After adding temporal information into traditional databases, a series of problems will be caused such as primary keys, indexes, referential integrity and so on. To solve these problems, it is suggested to add an intermediate module that becomes a bridge of communication between users and a traditional query language. Through this module, temporal types of instants, intervals and periods and temporal predicates can be converted into the data types and the operators that SQL is able to distinguish and carry out. Also, integrity constraints and referential constraints can be put into the module as the criterion of modification of databases. The advantages of the strategy include that the modification of traditional database theory is not involved; it is unnecessary to introduce additional software to implement it and bring about economic benefit; users do not need to largely modify their databases structure and their original application systems are not affected.