Data Model In DBMS And Its Types

Data Model

The Data Model in DBMS can give us an idea of what it will appear when it is fully implemented. It describes the data elements as well as the relationships between data elements. Data models are used to demonstrate the way data is stored, linked, accessed, and updated by the management of databases. In this instance, we employ symbols and texts to represent the information in a way that employees of the company can understand and communicate with the information. 

Two types of data modeling techniques

1. Entity Relationship (E-R) Model
2. UML (Unified Modelling Language)

There are numerous types of data models in use today however, this Relational model remains the best and most popular model in a common field. In addition to the Relational model, There are many different kinds of data models which we will explore the exact content more in-depth within this article. Some of the Types of Database Models in DBMS are

Types of Database Models in DBMS

1. Hierarchical Model
2. Network Model
3. Entity-Relationship Model
4. Relational Model
5. Object-Oriented Data Model
6. Object-Relational Data Model
7. Flat Data Model
8. Semi-Structured Data Model
9. Associative Data Model
10. Context Data Model

1.Hierarchical Model

The hierarchical model was one of the types of database model that was considered to be the initial DBMS model. The model organizes the information in a hierarchical structure. The hierarchy begins at the root, which contains the root data, and later expands into an expanding tree that adds child nodes on top of the main node. This model can easily represent certain real-world relationships like recipes for food, sitemaps for websites, and so on. An example: We can depict the relationship between shoes on a shopping website by following the following format:

Features

1. One-to-many relationships: The information here is organized in a tree-like arrangement with the one-to-many relationship being between the data types. In addition, there could be only one path from the parent and any of the nodes. Examples: In the above example, we would like to visit the node sneakers, we can only choose one route to get there i.e by way of the men’s shoe node.

2. Parent-Child Relationship Every child node is one parent node. However, the parent node may contain multiple child children. Multiple parents aren’t allowed.

3. Error in Deletion: If a parent node is deleted, the child node is also deleted.

4.PointersPointers serve to connect the parent node to the child node. They are utilized to move between stored information. Examples: In the above instance, the ‘ shoes‘ node links to two other nodes, namely the women’s shoe node, and the ‘ the men’s shoe the node.

Advantages of Hierarchical Data Model

• It’s easy and quick to move through the tree-like structure.
• Any change made to the parent node will be visible in the child node, ensuring that the integrity of the data is ensured.

DISADVANTAGE

• Complex relationships cannot be supported.
• Since it doesn’t allow multiple parents for the child node, so when we have a complex relationship in which the child node has to have two parent nodes then it isn’t possible to represent using this model.
• If a parent’s node is deleted, the child node is also removed.

2.Network Model

The model extends the hierarchy model. The model that was the most well-known model prior to it was replaced by the model of relational. It is the same model as the hierarchy model. The only difference is that records may have multiple parents. This model replaces the hierarchy tree with the graph. Examples: In the above example, we can see that the node child has parents i.e. CSE Department and Library. This was previously not feasible within the hierarchical model.

Essential Feature

1. Capability to join relationships: In this model, because the relationships are greater,, data will be more connected. This model can be used to handle one-to-one relationships as well as many-to-many relationships.
2. Multiple pathways: As there are more relationships, there could be more than one route into the record. This makes accessing data fast and easy.
3. Circular linked list: The operations on the network model are performed using this circular linked list. The current location is recorded by an application and the position is able to navigate through the records in accordance with the relation.

ADVANTAGES

• The data is accessible faster when opposed to the model of hierarchy. This is due to the fact that data is more connected in the network model . Additionally, there could be more than one route to get to a particular node. Therefore, the data can be accessed in a variety of ways.
• Since there is a relationship between a parent and child which means that data integrity is assured. Any changes in the parent records are recorded in the child’s record.

DISADVANTAGES

• As increasing numbers of relationships have to be managed, the system can become complex. Therefore, the user should have a thorough understanding of the model in order to work on the model.
• Changes like updation, deletion, or insertion are extremely complicated.

3. Entity-Relationship Data Model

Entity-Relationship Model or more commonly ER Model is a high-level diagram of a data model. The ER Model is a way to depict the real-world situation in a visual form that makes it easier for people who are involved to comprehend. It’s also easy for developers to grasp the system just by taking a look at it in the E-R diagrams. We employ the ER diagram to provide a visual representation of the ER Model. ER diagrams have the following three elements:

• Entities Entity can be described as an actual thing. It could be a location, a person or even a concept. Examples: Teachers, Students Building, Courses Department, and so on are some of the main entities of a school management system.
• attributes: A person has a real-world property known as an attribute. It is the characteristic of the attribute. Examples: The entity teacher is a teacher. It has properties like teacher ID, salary, age, etc.
• Relationship The term “relationship” describes how two characteristics are connected. Examples: Teacher works for an organization.

In the diagram above in the above diagram, in the above diagram, there is Teacher and Department. They have attributes like the Teacherentity include Teacher Name teacher_id, age the Salary, Mobile_Number. The attributes of the entity departments entity include Dept_id and Dept_name. Both entities are linked by the relation. Each teacher is employed in an organization.

FEATURES

• Graphical representation for Better Understanding It’s easy to comprehend and simple to grasp therefore it is a great tool to be used by developers to interact with stakeholders.
• Diagram of the ER: ER diagram is employed as a tool to represent the model.
• Data Design It aids database designers to create a database. It is extensively utilized in database design.

ADVANTAGES

• Easy: Conceptually ER Model is extremely simple to construct. If we can identify the relationship between attributes and entities, it is easy to create the ER Diagram of the model.
• An effective communication device This model is extensively used by database designers to assist in communicating their thoughts.
• Simple Conversion to Any Model The HTML0 model is well mapped with the model of a relational, and can easily be converted into a relational model by changing the E-R model into the table. The model can be transformed into any other model such as the hierarchical model, network model, etc.

DISADVANTAGES

• There are no industry-wide standards for notation It is not a standard industry-wide for the development of the ER model. Thus, one developer may utilize notations that aren’t accepted by other developers.
• Information is hidden: Certain information may be missing or hidden within the ER model. Since it’s a top-level model, there is a chance that specific details could be concealed.

4.Relational Model

The relational model is the most commonly used data model in DBMS. The basic rule of this model is, It is a model where the data is kept by way of two-dimensional tables. All information is stored in the form of rows and columns. The fundamental structure of a model that is relational is tables. Therefore the tables are known as relations within the relational model. Examples: In this example, there is an employee table.

FEATURES

• Tuples Each row within the table is known as the tuple. Each row is comprised of all the details regarding any particular instances of an object. In the example above each row is filled with all the details about a particular individual, similar to the way the first row, which contains details regarding John.
• Field or attribute: Attributes are the property that defines the table or relationship. The attributes’ values should come from within the exact domain. In the previous example, we have various aspects of an employee such as Salary and Mobile_no.

ADVANTAGES

• Easy: This model is less complex it is compared to the network model and hierarchical models.
• Flexible: This is a model that can scale easily to the extent that we add as many columns and rows as we’d like.
• Structural Independence It is possible to alter the structure of databases without altering the method used to get to data. If we are able to make changes to the structure of the database without altering the ability of DBMS for accessing the information, we are able to declare that structural independence is attained.

DISADVANTAGES

• Hardware Overheads For concealing the complexity and making life simpler for users, this model is more demanding of hardware and storage devices for data.
• Unstable Design Because the model of relationship is extremely easy to create and utilize. Users don’t need to be aware of how the information is stored for them to gain access to it. This design flexibility could result in the creation of a bad database, which could slow down as the database expands.

But these issues are insignificant when compared to the benefits that the model of relations. The problems could be avoided through the use of effective implementation and organization.

5.Object-Oriented Data Model

The real-world issues are more accurately represented in the model of data that is object-oriented. The model is based on the idea that both relationship and the data are contained as a single entity known as an object. You can save videos, audio, images, and more in databases that were not feasible in the relational model(although you could store video and audio in a relational database, it’s recommended not to store it in relational database Technology). This model has two more objects connected by hyperlinks. The link serves to link one object to other objects.

6. Object-Relational Model

It is a mixture of the relational model as well as the object-oriented model. The model was created to bridge gaps between object-oriented models as well as the relational model. There are several advanced features such as we can create complicated data types to meet our needs using available data types. The issue in this particular model is it could become complicated and challenging to manage. Thus, a clear understanding of the model is necessary.

7. Flat Data Model

It is a basic model where the database is presented as a table composed of columns and rows. To access any information the computer must scan every row and column. This results in the mode becoming extremely slow as well as inefficient.

8. Semi-Structured Model

A semi-structured model is a modified version of the model of relationships. We are unable to differentiate between schema and data in this model. Example: Web-Based data sources that we are unable to distinguish between schema and data of the site. 

This model is based on the assumption that certain entities may not have the attributes they need and others could include an additional attribute. This model is flexible in the storage of information. It also offers flexibility to the attributes. 

This model is where the structure information that is usually in the schema of the database is integrated into its data. The distinction between schema and data is ambiguous at best. This model is helpful for explaining systems, like the Web-based sources of data, that we consider to be databases, but are not able to be governed by the schema. 

It is also helpful for describing the interactions among databases that do not conform to an identical schema. Examples: If we are saving any value within any attribute, that value could be either an atomic value or a set of values.

9. Associative Data Model

Associative Data Model refers to a type of model where the data is divided into two components. Everything that has an independent existence is referred to as an entity and the relationship between the entities is known as the association. The information broken down into two parts are known as links and items.

• Items The items contain names and an identifier(some numerical value).
• Link: Link contains the identification number of the source, verb, verb, and subject.

An example Let’s take a look at a statement that reads “The world cup is being hosted by London from 30 May 2020”. In this information, two links must be saved:

1. World Cup is currently being hosted by London. The word that is used here is “the world cup” and the verb “is in existence” and the goal is London..
2. …from 30 May 2020. The source is the link from before and from where the verb is “from”, and the goal is 30 May 2020′.

Other Common Database models of databases

Numerous other databases have been or are being used. within this content item

Model of a file that is reversed

A database that is built using the inverted structure of files is designed to speed up full-text searches. In this structure, the data is indexed as a sequence of keys inside the lookup table, and the results point to the location of related files. This type of structure could provide almost immediate reports in big data analytics and big data for instance.

It has been utilized in software called the ADABAS Database Management System developed by Software AG since 1970 and is still in use to this day.

Flat model

Flat models are the oldest and simplest model for data. It lists all information in one table, which is composed of rows and columns. To access or modify the data, the computer needs to load every flat data file making this model unsuitable for any but the smallest data sets.

Multidimensional model

This is a variation of the relational model developed to improve analytical processing. The relational model is designed to work with online transactions (OLTP) This model is specifically designed to facilitate Online Analytic Processing (OLAP).

Each cell of the dimensional database holds information regarding the dimension table this model is useful in developing a conceptual design for the database diagram this model is useful in developing a conceptual design for the database.

This model is useful in developing a conceptual design for the database. This model is useful in developing a conceptual design for the database. tracked through the databases. Visually, it’s an array of cubes instead of tables with two dimensions.

Context model

The model is able to include elements from other database models as required. It combines elements from semistructured, object-oriented networks, and object-oriented models.

Model of Associative

The model categorizes all information points according to the fact that they are either entities or associations. According to this theory, an “entity” refers to anything that exists in isolation while an association is anything that exists in relation to another.

The associative model organizes it into two groups:

• A set of things that have a distinct identifier, a title, and a classification
• A collection of hyperlinks each of which has a distinct identification number and distinctive identifiers of the verb, source, and the target. The fact stored refers to what is the origin, the three identifiers could be referring to a link or to an item.

Other less well-known database models are:

• Semantic model, which contains details about how the data is related to the real world
• XML database that permits data to be defined and even saved in XML format
• Named graph
• Triplestore

NoSQL database models

Alongside objects database models different non-SQL models have also emerged in opposition from the traditional model

This is the graph model database is better than a model for networks, allows any node to be connected to any other.

It is a multivalue model that breaks away apart from the model that is relational, by allowing attributes to hold more data in a list rather than just one data element.

The document model is a Document model is intended for the storage and management of documents or semi-structured information, instead of atomic data.

Databases on the Web

The majority of websites use databases to manage and present information to their users. If someone is using the search features on these websites then their search queries are transformed into queries that the database server processes. Typically middleware links the server on the internet to the database.

The vastness of databases makes them able to be used in virtually every field, from online shopping to targeting a specific voter segment for the political campaign. Different industries have created their own rules for the design of databases, including air transportation and vehicle manufacturing.

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