Evolution of Database models
Database management systems were initially introduced throughout 1960 and have continued to evolve throughout resultant decades. Some combination of the subsequent 3 objectives forever drove the event and evolution of information technology.
- Providing greater autonomy between programs and data.
- To manage increasingly complex data types and structures.
- To provide easier and faster access to data for non-computer professionals.
First Generation DBMS’s
The hierarchical and network database management systems (generally regarded as the first-generation DBMS) were developed to cope with increasingly complex data structures. Both approaches to database structure used physical pointers or disk addresses to relate records in deferent files.
|Hierarchical database model||Network database model|
|Very simple and organized as a family tree structure||Complex and organized as a network structure|
|One to many relationships||Many to many relationships|
|The whole database depends on root record||The database does not depend on a root record|
|The topmost record is the root record||Many records at the top level|
|Single access path for a data record||Multiple access paths for a data record|
|The data record can be duplicated||Data records are not duplicated|
|Access using navigational record at a time procedure||Access using navigational record at a time procedure|
|We need to write complex queries to get information from multiple branches. No cross-links||Can write simple queries to get information from multiple branches because cross-links are available|
The hierarchical database model was developed to overcome the limitations of the file processing system and the Network model has derived as a solution to problems caused by the Hierarchical model. And both have the following problems.
- Difficult access to data, based on the navigational record at a time procedure.
- Very limited data independence.
- No widely accepted theoretical foundation for either model.
Relational Data Model (Second Generation DBMS’s)
In the 1970s, the E.F Codd and others worked to improve the relational data model. This model was considered a second-generation DBMS in the 1980s. It also received wide commercial recognition.
In the Relational Data Model, all data are represented in tables. It is base on logical relationships in data, overcome the problems of physical address handling. It is based on mathematical theory and therefore has a solid mathematical foundation. A relatively simple fourth generational language called SQL is used for data retrieval.
- Data Structure: Data are stored in the form of a tabular structure.
- Data Manipulation: In here this uses a powerful operation to manipulate data.
- Data Integrity: There are facilities to ensure data integrity.
What we can introduce relation is a two-dimensional table consisting of rows and columns of data. Each relationship is a tuple group consisting of a named column and a number of arbitrary rows. Each connection row corresponds to a record containing the values for the object.
Properties of a Relation
- There must be a unique name for each relation in a database
An entry at the intersection of every row and column is automatic or single-valued. (no ambiguous attributes are allowed).
- Each tuple should be distinctive. No 2 rows in an exceeding relation area unit identical.
- Each attribute (or column) inside a table features a distinctive name.
The sequence of columns (left to right) is insignificant.
The relational data model includes several types of constraints or business rules, whose purpose is to maintain the accuracy and integrity of data in the database. The following shows the major types of integrity constraints
All of the worth that seems in a very column of a relation should be taken from a similar domain. A domain is a valid set of values that may be assigned to an attribute. Domain integrity can be maintained by the use of
- User-defined domain types
- Not Null
- Default value
- Check clause
The entity integrity rules area unit designed to assure that each relation features a primary key, and it guarantees that each primary key attribute isn’t null. That is the info values for that primary key are all valid.
A referential integrity constraint may be a rule that maintains consistency among the rows of 2 relations. In the relational data model, relationships between tables are defined using foreign keys. The rule states that if there’s a foreign key in one relation, either every foreign key worth should match a primary key worth in referred relation or the foreign key value must be null. That is values of a foreign key must be defined from the primary key domain or null referencing relation is having the primary key of the referred to as the foreign key.
What is Next?
You can learn Database Design in the next lesson.
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