Data models Early approaches to data organization

Data structures Network databases were, in a sense, a development of hierarchical systems. If in a hierarchical structure a descendant record must have exactly one ancestor, then in a network data structure a descendant may have any number of ancestors (Fig. 5.3). The terms descendant and ancestor in relation to data records in hierarchical and networked systems reflect the fact that in these systems data records are associated with each other by reference to an address, and not by data value. The basic concepts of network databases include: level, element (node), connection.

Fig. 5.3 Structure of the network database

Data manipulation operators perform low-level navigation through the network structure, using links to move from one record to another. In the network structure, each element can be associated with any other element, since the logic of the data selection procedure depends on the physical organization of this data, this model is not completely independent of the application. Operations on data:

• ADD - make an entry in the database;
• INCLUDE INTO GROUP RELATIONSHIP - associate an existing subordinate record with the owner-record;
• SWITCH - link an existing subordinate entry to another owner-record in the same group relation;
• UPDATE - change the value of the elements of the previously extracted record;
• REMOVE - extract records sequentially by key value;
• DELETE - remove the record from the database.

Integrity constraints are not generally supported. As in the hierarchical model, only maintaining integrity by reference is provided (the owner of the relationship is a member of the relationship).

A common feature of all early channeling systems is that they are not based on any abstract data models supported by the corresponding mathematical apparatus. Moreover, the very concept of a data model as applied to database systems began to be used precisely with the advent of the relational approach, which was largely born from an analysis of the features, advantages and, to a large extent, disadvantages of the existing data management systems.

In early systems, access to data in the database was carried out directly at the record level. The database navigation, search, selection and recording of data in these systems were carried out by the user using standard procedural programming languages, expanded by the functions of working with the DBMS, requiring the user to understand the low-level features of data storage and the connections between them. The possibility of interactive access to data was realized much more limited only by creating appropriate application software. As already mentioned, early systems had rather weak means of maintaining data integrity.

Low-level means of navigation and data manipulation made it possible, however, in early systems to ensure high efficiency of the implementation of these functions by application programs and the economical use of the memory of the computing system. This can be attributed to the advantages of such systems, especially given the level of computing systems of the time (1960-70s). One of the consequences of the low level of language tools used in these models for working with data was the complexity of creating application software systems and the need to know the features of physical presentation and data storage. Ultimately, this led to greater complexity or even the impossibility of fulfilling a set of requirements for information systems with databases, discussed in previous sections, for example, implementing the requirements of multidimensional data use, ensuring data independence from the logic of the programs using them, etc.