Record Based Data Model – Difference between Hierarchical, Network and Relational Model

Hello, friends. Today we will learn about the Record based data model. Which we learn about difference between hierarchical model, network model, and relational model. So let us get started.

Record based data model

Friends hierarchical model, network model, and relational model are record-based data models. It is also known as ‘Representational Data Model‘. It used most frequently in traditional DBMS. These models are used in describing data at the conceptual view levels. Before knowing about all these data models, we need to have brief information about them, so let’s know about it.

Hierarchical Data Model

Hierarchical model is one of the oldest database models. The hierarchical model became popular with the introduction of IBM’s Information Management System (IMS), which is the only viable commercial hierarchical database still in use today, mainly on old mainframe computers. The concept for the hierarchical model was initially based on a bill of Materials (BOM).

The hierarchical data model organizes records in a tree structure, i.e., hierarchy of parent and child records relationship. This model employs two main concepts: Record and Parent-Child Relationship. A record is a collection of field values that provide information about an entity.

A Parent-Child Relationship type is a 1:N relationship between two record types. The record type on one side is called the parent record type, and the one on the N side is called the child record type. In terms of tree data structure, a record type corresponds to the node of a tree, and a relationship type corresponds to the edge of the tree.

Network Data Model

As a result of limitations in the hierarchical model, designers developed the Network Model. The ability of this model to handle many to many (M: N) relations between its records is the main distinguishing feature from the hierarchical model or, in other words, we can say that his model permits a child record to have more than one parent. In this model, directed graphs are used instead of tree structure in which a node can have more than one parent. This model was designed to handle non-hierarchical relationships.

For example, A book database where an author can have many books and a book could have more than one author.

The relationships between specific records of 1:1 (one to one), 1:N (one to many) of M: N (many to many) are explicitly defined in database definition of this model.

The Network Model was standardized as the CODASYL DBTG (Conference of Data System Language, Database Task Group) model.

There are two basic data structures in this model – Records and Sets. The record contains detailed information regarding the data, which are classified into record types. A set type represents a relationship between record types, and this model use linked lists to represent these relationships. Each set type definition consists of three essential elements: a name for set type, an owner record type (like a parent), and a member record type (like a child).

To represent many to many relationships in this model, the relationship is decomposed into one to many (1:N) relationships by introducing an additional record type called an Intersection Record of Connection Record.

Relational Data Model

The Relational Model is considered one of the most popular developments in database technology because it can represent most real-world objects and their relationships.

The main significance of the model is the absolute separation of the logical view and the physical view of the data. The physical view in the relational model is implementation-dependent and not further defined.

The logical view of data in the relational model is set-oriented. A relational set is an unordered group of items; the field in the items are the columns. The column in a table has names. The rows are unordered and unnamed. A database consists of one or more tables plus a catalog (represented by tables) describing the database.

The relational model consists of three components

1. A structural component – A set of tables (also called RELATIONS) and a set of domains that define how data can be represented (data structure).
2. A set of rules for maintaining the integrity of the database.
3. A manipulative component consisting of a set of high-level operation which acts upon and produces whole tables.

In the relational model, the data is represented in tables used interchangeably with the word Relation. Each table consists of rows, also knowns as tuples, and columns, also known as attributes. Relationships are existing between different tables. This model does not require any information that specifies how the data should be stored physically.

A relational database is defined as a group of independent tables linked to each other using some common fields of each related table.

The Relational Database possesses the following properties

• Data is represented in the form of tables.
• It is only concerned with the data but not the physical storage details.
• It enables the computer systems to handle the queries efficiently.
• Each table at the intersection of each row and column one and only one value can be stored.
• It provides information about the metadata, i.e., contents and structure in system tables.
• Tables can be joined, and the result itself is a table.
• Tuples in a relation do not have any particular order.

Difference between Hierarchical, Network and Relational Data Model

Hierarchical Data Model

1. Organizes the record in a tree structure, i.e., hierarchy of parent and child record relationships.

Network Data Model

1. Organizes the collection of records connected through links or pointers, which is an association between two records.

Relational Dat Model

1. Records are represented in the form of a table, and relationships between the tables are set using common fields.

Hierarchical Data Model

2. Only one-to-one (1:1) and one-to-many (1:N) relationships can be implemented in this model.

Network Data Model

2. In addition to (1:1) and (1:N), many to many relationships can also be implemented.

Relational Data Model

2. All the relationships can be implemented easily.

Hierarchical Data Model

3. It organizes records in the form of tree structure.

Network Data Model

3. It organizes records in the form of directed graphs.

Relational Data Model

3. It organizes records in the form of tables.

Hierarchical Data Model

4. Relations among records are physically implemented using pointers.

Network Data Model

4. Relations among records are represented physically using linked lists.

Relational Data Model

4. Relations among records are represented logically in the form of rows and columns.

Hierarchical Data Model

5. Lack of declarative querying facilities.

Network Data Model

5. Lack of declarative querying facilities.

Relational Data Model

5. Provides declarative querying facilities using SQL.

Hierarchical Data Model

6. Complexity makes the design of database difficult.

Network Data Model

6. Complexity increases the burden on the programmer for database design as well as data manipulation.

Relational Data Model

6. As physical level details are hidden from end-users, this model is straightforward to understand.

Hierarchical Data Model

7. Insertion anomaly exists, i.e., Insertion of a child record without parent record is not possible.

Network Data Model

7. This model does not suffer from insertion anomaly.

Relational Data Model

7. This model does not suffer from insertion anomaly. It is effortless to insert records into the tables.

Hierarchical Data Model

8. Multiple occurrences of child record leads to inconsistency problems when updation is performed.

Network Data Model

8. Due to single occurrences of records, no update problem exists.

Relational Data Model

8. Using normalization, the redundancy of data is removed; hence updation is very easy to perform.

Hierarchical Data Model

9. Deletion anomaly exists. It is difficult to delete the parent records.

Network Data Model

9. No deletion anomaly exists as simple changing position pointers can be made when record is deleted.

Relational Data Model

9. Free from deletion anomaly because information or records are stored in different tables.

Hierarchical Data Model

10. Retrieval algorithms are complex and asymmetric.

Network Data Model

10. Retrieval algorithms are complex but symmetric.

Relational Data Model

10. Retrieval algorithms are simple and symmetric.

Hierarchical Data Model

11. IBM’s IMS (Information Management System) is a popular DBMS using this model.

Network Data Model

11. VAX-DBMS, DMS-1100 of UNIVAC and SUPRA DBMS’s use this Model.

Relational Data Model

11. Most commonly used in real-world applications. Oracle. SQL Server, Sybase DBMS use this model.

Hierarchical Data Model

12. Less data independence.

Network Data Model

12. Partial data independence.

Relational Data Model

12. Data independence.

Hierarchical Data Model

Network Data Model

Relational Data Model