t component of these data!
             base systems were the static association of certain data sets (files) with individual programs that would concentrate on these. There were high redundancy problems between files; inconsistencies when one program made changes that are not made in all programs; inflexibility against changes in applications; low productivity by programmers since program maintenance was expensive; and the problem of adopting and maintaining standards for coding and data formats. The third generation, pre-relational databases, started in the 1960s and continued into the 1970s. This generation is characterized by the introduction of a distinction between logical and physical information, along with a parallel need to manage large collections of data. Data models were used for the first time to describe physical structures from a logical point of view. With this distinction between the logical and physical information, value systems were developed which could integrate all the data of a given applica!
             tion into one collection. The fourth generation consisted of relational databases and began in the 1980s, resulting in database systems that could store data redundancy free under a central control and in a clear distinction between physical and a logical data model. Systems based on relationship modeling occurred during this period of time. The systems based on relationship modeling are provided with a high degree of physical data independence and the availability of powerful languages. Less of the system is visible to the user, with changes taking place in the background. A shift from record orientation to set orientation marks this fourth generation. As of 1991, there was a fifth generation predicted, post-relational, which we are currently experiencing, and perhaps surpassing. Other applications can benefit from database technology. The development of extensible systems, logic-oriented systems, and object-oriented systems are p...