Bi-Temporal Implementation In Relational Database Management Systems: MS SQL Server

Abstract. Traditional database management systems (DBMS) are the computation storage and reservoir of large amounts of information. The data accumulated by these database systems is the information valid at present time, valid now. It is the data that is true at the present moment. Past data is the information that was kept in the database at an earlier time, data that is hold to be existed in the past, were valid at some point before now. Future data is the information supposed to be valid at a future time instance, data that will be true in the near future, valid at some point after now. The commercial DBMS of today used by organizations and individuals, such as MS SQL Server, Oracle, DB2, Sybase, Postgres etc., do not provide models to support and process (retrieving, modifying, inserting and removing) past and future data. The implementation of bi-temporal modelling in Microsoft SQL Server is important to know how relational database management system handles data the bi-temporal property. In bi-temporal database, data saved is never deleted and additional values are always appended. Therefore, the paper explores one of the way we can build bitemporal handling of data. The paper aims to build the core concepts of bi-temporal data storage and querying techniques used in bi-temporal relational DBMS i.e., from data structures to normalized storage, and to extraction or slicing of data. The unlimited growth of data results relational data to become complicated in terms of management and storage of data. Thus, the developers working in various commercial and industrial applications should know how bi-temporal concepts apply to relational databases, especially due to their increased flexibility in the bi-temporal storage as well as in analyzing data. Thereby, the paper demonstrates how bi-temporal data structures and their operations are applied in Relational Database Management System. Keywords: Bi-temporal Databases, Databases, Normalization, MS SQL Server Bitemporal Databasehttps://sites.google.com/site/ijcsis/vol-19-no-3-mar-202