The document discusses several database management system (DBMS) models:
- Relational, network, hierarchical, object-oriented, and object-relational models are described as the main DBMS models.
- Key aspects of each model are covered, including data structure, relationships, querying capabilities, and advantages/disadvantages.
- Examples are provided for the relational model in the form of a sample table and for the hierarchical model in terms of its data structure and relationships.
- Overall the document provides a high-level overview and comparison of the main DBMS models.
This chapter discusses the relational database model and its basic components. It explains that the relational model provides a logical view of data organized into tables composed of rows and columns. Each row must be uniquely identifiable through a primary key. Tables can be linked together through common attributes, and relationships between entities can be modeled as one-to-one, one-to-many, or many-to-many. The chapter also covers relational operators, keys, data integrity rules, and how to handle data redundancy and indexing in a relational database.
The document presents information on Entity Relationship (ER) modeling for database design. It discusses the key concepts of ER modeling including entities, attributes, relationships and cardinalities. It also explains how to create an Entity Relationship Diagram (ERD) using standard symbols and notations. Additional features like generalization, specialization and inheritance are covered which allow ERDs to represent hierarchical relationships between entities. The presentation aims to provide an overview of ER modeling and ERDs as an important technique for conceptual database design.
The document discusses database design and the design process. It explains that database design involves determining the logical structure of tables and relationships between data elements. The design process consists of steps like determining relationships between data, dividing information into tables, specifying primary keys, and applying normalization rules. The document also covers entity-relationship diagrams and designing inputs and outputs, including input controls and designing report formats.
A web database allows storing and accessing data via the internet. It uses a client-server architecture with a web interface to connect to backend database servers. Large businesses rely on web databases to store customer information and make it accessible online. Web databases provide platform independence and standardization through their use of web technologies like HTML. Their future involves new technologies like NoSQL, Hadoop, universal memory and blockchain.
The document discusses database management systems and their advantages over traditional file systems. It covers key concepts such as:
1) Databases organize data into tables with rows and columns to allow for easier querying and manipulation of data compared to file systems which store data in unstructured files.
2) Database management systems employ concepts like normalization, transactions, concurrency and security to maintain data integrity and consistency when multiple users are accessing the data simultaneously.
3) The logical design of a database is represented by its schema, while a database instance refers to the current state of the data stored in the database tables at a given time.
The document discusses the entity-relationship (ER) model for conceptual database design. It describes the basic constructs of the ER model including entities, attributes, relationships, keys, and various modeling choices. The ER model is useful for capturing the semantics of an application domain and producing a conceptual schema before logical and physical design.
This document discusses database languages used in database management systems (DBMS). It describes three types of database languages: data definition language (DDL) used to define and modify the database schema; data manipulation language (DML) used to insert, update, delete and retrieve data; and data control language (DCL) used to control access privileges. Examples are provided for common statements in each language type like CREATE, ALTER, DROP for DDL and INSERT, UPDATE, DELETE, SELECT for DML. Case sensitivity and data types are also briefly covered.
This chapter discusses the relational database model and its basic components. It explains that the relational model provides a logical view of data organized into tables composed of rows and columns. Each row must be uniquely identifiable through a primary key. Tables can be linked together through common attributes, and relationships between entities can be modeled as one-to-one, one-to-many, or many-to-many. The chapter also covers relational operators, keys, data integrity rules, and how to handle data redundancy and indexing in a relational database.
The document presents information on Entity Relationship (ER) modeling for database design. It discusses the key concepts of ER modeling including entities, attributes, relationships and cardinalities. It also explains how to create an Entity Relationship Diagram (ERD) using standard symbols and notations. Additional features like generalization, specialization and inheritance are covered which allow ERDs to represent hierarchical relationships between entities. The presentation aims to provide an overview of ER modeling and ERDs as an important technique for conceptual database design.
The document discusses database design and the design process. It explains that database design involves determining the logical structure of tables and relationships between data elements. The design process consists of steps like determining relationships between data, dividing information into tables, specifying primary keys, and applying normalization rules. The document also covers entity-relationship diagrams and designing inputs and outputs, including input controls and designing report formats.
A web database allows storing and accessing data via the internet. It uses a client-server architecture with a web interface to connect to backend database servers. Large businesses rely on web databases to store customer information and make it accessible online. Web databases provide platform independence and standardization through their use of web technologies like HTML. Their future involves new technologies like NoSQL, Hadoop, universal memory and blockchain.
The document discusses database management systems and their advantages over traditional file systems. It covers key concepts such as:
1) Databases organize data into tables with rows and columns to allow for easier querying and manipulation of data compared to file systems which store data in unstructured files.
2) Database management systems employ concepts like normalization, transactions, concurrency and security to maintain data integrity and consistency when multiple users are accessing the data simultaneously.
3) The logical design of a database is represented by its schema, while a database instance refers to the current state of the data stored in the database tables at a given time.
The document discusses the entity-relationship (ER) model for conceptual database design. It describes the basic constructs of the ER model including entities, attributes, relationships, keys, and various modeling choices. The ER model is useful for capturing the semantics of an application domain and producing a conceptual schema before logical and physical design.
This document discusses database languages used in database management systems (DBMS). It describes three types of database languages: data definition language (DDL) used to define and modify the database schema; data manipulation language (DML) used to insert, update, delete and retrieve data; and data control language (DCL) used to control access privileges. Examples are provided for common statements in each language type like CREATE, ALTER, DROP for DDL and INSERT, UPDATE, DELETE, SELECT for DML. Case sensitivity and data types are also briefly covered.
This document discusses different database models including hierarchical, network, entity-relationship, and relational models. The hierarchical model organizes data in a tree-like structure with parent-child relationships. The network model extends the hierarchical model by allowing nodes to have more than one parent. The entity-relationship model divides data into entities and attributes and represents relationships visually. The relational model, introduced by E.F. Codd in 1970, organizes data into two-dimensional tables related through common fields and is the most widely used database model today.
This document provides an overview of databases and database management systems (DBMS). It discusses how databases evolved from file systems to address flaws in data management. It describes what a DBMS is and its functions in managing the database structure and controlling data access. The document also summarizes different database models including hierarchical, network, relational, entity-relationship, and object-oriented models. It highlights advantages and disadvantages of each model.
This document discusses different data models used in database management systems including record-based, relational, network, hierarchical, and entity-relationship models. It provides details on each model such as how data is organized. A record-based model uses fixed-length records and fields. The relational model organizes data into tables with rows and columns. The network model links entities through multiple paths in a graph structure. The hierarchical model arranges data in a tree structure. Finally, the entity-relationship model views the real world as entities and relationships between entities.
Entity Relationship Diagrams (ERDs) are used to model relationships between entities in a database. The document discusses ERD components like entities, relationships, cardinality, and attributes. It provides an example of an ERD for a company with departments, supervisors, employees, and projects. Key entities are identified and their relationships and attributes are represented in the example ERD diagrams.
A distributed database is a collection of logically interrelated databases distributed over a computer network. A distributed database management system (DDBMS) manages the distributed database and makes the distribution transparent to users. There are two main types of DDBMS - homogeneous and heterogeneous. Key characteristics of distributed databases include replication of fragments, shared logically related data across sites, and each site being controlled by a DBMS. Challenges include complex management, security, and increased storage requirements due to data replication.
The document discusses data modeling and different data models. It describes the evolution of data models from hierarchical to network to relational models. It also covers the entity relationship and object-oriented models. The key points are that data modeling helps reconcile different views of data, business rules inform database design, and the conceptual model provides an integrated global view of the database.
Normalisation is a process that structures data in a relational database to minimize duplication and redundancy while preserving information. It aims to ensure data is structured efficiently and consistently through multiple forms. The stages of normalization include first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), fourth normal form (4NF) and fifth normal form (5NF). Higher normal forms eliminate more types of dependencies to optimize the database structure.
The document discusses different types of databases and database applications, including numeric/textual databases, multimedia databases, geographic information systems, data warehouses, and real-time databases. It also defines key database concepts such as database, data, mini-world, and database management system. Database systems are used to store and manage large volumes of structured data and provide functionality for defining data structures, querying and manipulating data, concurrent access, security, and more. Examples of database applications include a university student information system and a large tax filing database.
This document provides information about an upcoming SQL Saturday Night event on March 30, 2013 that will focus on using T-SQL. The presentation will be recorded so that those unable to attend can view it later. Attendees are asked to change their virtual cards to a specific color if they are unable to hear the presenter. The presentation will be free and begin in 1 minute.
Database architecture uses programming languages to design software for businesses, focusing on designing, developing, implementing, and maintaining computer programs. The architecture of a database system depends on the computer system it runs on, and a database system can be centralized or use a client-server model with client machines for users and a server for the database system.
The document provides an overview of databases and database design. It defines what a database is, what databases do, and the components of database systems and applications. It discusses the database design process, including identifying fields, tables, keys, and relationships between tables. The document also covers database modeling techniques, normalization to eliminate redundant or inefficient data storage, and functional dependencies as constraints on attribute values.
The relational database model offers a logical view of data based on relations composed of rows and columns. Relations are implemented as tables with primary keys to uniquely identify rows. Tables are linked through common attributes and operations like joins. Good design involves identifying entity relationships like one-to-one, one-to-many, and many-to-many and normalizing them.
Dbms classification according to data modelsABDUL KHALIQ
CLASSIFICATION ACCORDING TO DATA MODELS
Hierarchal Model
In a hierarchical data model, data are organized into a tree-like structure.
Network Model
based on an enlargement of the concept of hierarchical data bases.
Relational Model
Data are stored in tables
Object Oriented model
Object oriented data base systems are the most recent development in data base technology.
Introduction
Definations
Advantages and Disadvantages
PowerPoint Presentation
PowerPoint Presentation for free
Dbms architecture
Three level architecture is also called ANSI/SPARC architecture or three schema architecture
This framework is used for describing the structure of specific database systems (small systems may not support all aspects of the architecture)
In this architecture the database schemas can be defined at three levels explained in next slide
This document discusses database normalization through various normal forms. It defines key concepts like functional dependencies and full functional dependencies. It explains the objectives and rules of first, second, third normal forms and BCNF. First normal form requires each field to contain a single value. Second normal form requires fields to depend on the whole primary key. Third normal form and BCNF further eliminate transitive dependencies. The document provides examples to illustrate normalization and resolving anomalies through decomposition. It also introduces multi-valued dependencies and fourth normal form.
The document discusses different methods of organizing computer files, including heap files, sequential files, indexed-sequential files, inverted list files, and direct files. It provides details on each method, such as how records are stored and accessed, their advantages and disadvantages, and examples. Key aspects covered include unordered storage in heap files, ordered storage and efficient sequential access in sequential files, indexed access for both sequential and random access in indexed-sequential files, and direct calculation of record locations in direct files.
The document discusses key concepts related to databases and database management systems. It defines a database as a collection of organized data and a database management system as a computer program that allows for creating, accessing, managing and controlling databases. It describes three common data models - relational, network and hierarchical - and explains some fundamental database concepts like tables, keys, relations and normalization.
This document defines database and DBMS, describes their advantages over file-based systems like data independence and integrity. It explains database system components and architecture including physical and logical data models. Key aspects covered are data definition language to create schemas, data manipulation language to query data, and transaction management to handle concurrent access and recovery. It also provides a brief history of database systems and discusses database users and the critical role of database administrators.
A database administrator is responsible for installing, configuring, upgrading, administering, monitoring and maintaining databases. Key responsibilities include database design, performance and capacity issues, data replication, and table maintenance. DBAs ensure proper data organization and management through their skills in SQL, database design, and knowledge of database management systems and operating systems. There are several types of DBAs based on their specific roles like system DBA, database architect, and data warehouse administrator.
Student POST Database processing models showcase the logical s.docxorlandov3
Student POST:
Database processing models showcase the logical structure of a database. The most commonly used model is the Relational database model that sorts the data in a table that consist of rows and columns. The column holds the attributes of the entity and rows hold the data of a particular instance of the entities. The major advantage of the Relational model is that it is in the table form and hence easier for users to understand, manage and work with the data. And, with the primary key and foreign key concepts, the data can be uniquely identified, stored in different entities and retrieved effectively with the relationships. The other advantage is that with the relational model, SQL language can be used to work with the data which is simple to understand and most widely used. The disadvantage of relational model could be the financial cost that is higher in comparison as the specific software needs to be in place and the regular maintenance needs to be performed that requires highly skilled manpower. And, the complexity of the database can be further increased when the volume of the data keep in increasing. Also, there is the limitation in the length of fields stored as different data types in relational model (Joseph & Paul, 2009).
The other processing model is the Object-oriented model that depicts database as the collection of objects. The advantage of this model is that it is compatible to work with complex data sets with the use of Object IDs and object-oriented programming. It’s disadvantage is that object databases are not commonly used and the complexity can hamper the performance of database. The other type of database model is the Entity-Relationship model which is mostly used for the conceptual design of database. It pictures the entities, several attributes that falls within the domain of that entity and the cardinality of relationship between them. It’s advantage is that the E-R diagram is easily understandable by the users at the first glance and thus can effectively work with the data in no time and can point out the discrepancies in the data. The other advantage is that it can be easily converted to other models if required by the business. The disadvantage of Entity-Relationship is that the industry standard notations for the diagram is not defined and thus can create confusion to the users. This model is only suitable for high-level database design (S.J.D.,2020).
2Nd Student POST :
Database models or commonly referred to as schemas help represent the structure of a database and its format which is run by a DBMS. Database model uses vary depending on user specifications.
Types of database models
1.
Network model
This network model uses a structure similar to that of a hierarchical model. The model permits multiple parents, which is a tree-like structure model. This model emphasizes two basic concepts; records and sets. Records hold file hierarchy and sets define the many-to-many relationship .
A database model refers to the structure of a database and determines how the data within the database can be organized and manipulated. Let’s explore some common types of database models:
Relational Model: The most popular example, the relational model, organizes data into tables (also known as relations). Each table contains rows representing records and columns representing attributes. Relationships between tables are established using keys.
Hierarchical Model: Developed by IBM for IMS (Information Management System), this model arranges data in a tree-like structure. Each record is a tree node, and relationships follow a one-to-many pattern. It’s predictable and efficient for data access.
Network Model: This model allows many-to-many relationships between records. It’s more flexible than the hierarchical model but less common.
Entity–Relationship Model (ER Model): It represents entities, their attributes, and the relationships between them. ER diagrams visually depict these components.
Object Model: Used in object-oriented databases, it treats data as objects with properties and methods. It’s suitable for complex data structures.
Document Model: Commonly used in NoSQL databases, it stores data as documents (e.g., JSON or XML). Each document can have varying attributes.
Entity–Attribute–Value (EAV) Model: A flexible model where data is stored in a sparse matrix. It’s useful for handling dynamic attributes.
Star Schema: Primarily used in data warehousing, it simplifies complex data structures into a central fact table connected to dimension tables.
This document discusses different database models including hierarchical, network, entity-relationship, and relational models. The hierarchical model organizes data in a tree-like structure with parent-child relationships. The network model extends the hierarchical model by allowing nodes to have more than one parent. The entity-relationship model divides data into entities and attributes and represents relationships visually. The relational model, introduced by E.F. Codd in 1970, organizes data into two-dimensional tables related through common fields and is the most widely used database model today.
This document provides an overview of databases and database management systems (DBMS). It discusses how databases evolved from file systems to address flaws in data management. It describes what a DBMS is and its functions in managing the database structure and controlling data access. The document also summarizes different database models including hierarchical, network, relational, entity-relationship, and object-oriented models. It highlights advantages and disadvantages of each model.
This document discusses different data models used in database management systems including record-based, relational, network, hierarchical, and entity-relationship models. It provides details on each model such as how data is organized. A record-based model uses fixed-length records and fields. The relational model organizes data into tables with rows and columns. The network model links entities through multiple paths in a graph structure. The hierarchical model arranges data in a tree structure. Finally, the entity-relationship model views the real world as entities and relationships between entities.
Entity Relationship Diagrams (ERDs) are used to model relationships between entities in a database. The document discusses ERD components like entities, relationships, cardinality, and attributes. It provides an example of an ERD for a company with departments, supervisors, employees, and projects. Key entities are identified and their relationships and attributes are represented in the example ERD diagrams.
A distributed database is a collection of logically interrelated databases distributed over a computer network. A distributed database management system (DDBMS) manages the distributed database and makes the distribution transparent to users. There are two main types of DDBMS - homogeneous and heterogeneous. Key characteristics of distributed databases include replication of fragments, shared logically related data across sites, and each site being controlled by a DBMS. Challenges include complex management, security, and increased storage requirements due to data replication.
The document discusses data modeling and different data models. It describes the evolution of data models from hierarchical to network to relational models. It also covers the entity relationship and object-oriented models. The key points are that data modeling helps reconcile different views of data, business rules inform database design, and the conceptual model provides an integrated global view of the database.
Normalisation is a process that structures data in a relational database to minimize duplication and redundancy while preserving information. It aims to ensure data is structured efficiently and consistently through multiple forms. The stages of normalization include first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), fourth normal form (4NF) and fifth normal form (5NF). Higher normal forms eliminate more types of dependencies to optimize the database structure.
The document discusses different types of databases and database applications, including numeric/textual databases, multimedia databases, geographic information systems, data warehouses, and real-time databases. It also defines key database concepts such as database, data, mini-world, and database management system. Database systems are used to store and manage large volumes of structured data and provide functionality for defining data structures, querying and manipulating data, concurrent access, security, and more. Examples of database applications include a university student information system and a large tax filing database.
This document provides information about an upcoming SQL Saturday Night event on March 30, 2013 that will focus on using T-SQL. The presentation will be recorded so that those unable to attend can view it later. Attendees are asked to change their virtual cards to a specific color if they are unable to hear the presenter. The presentation will be free and begin in 1 minute.
Database architecture uses programming languages to design software for businesses, focusing on designing, developing, implementing, and maintaining computer programs. The architecture of a database system depends on the computer system it runs on, and a database system can be centralized or use a client-server model with client machines for users and a server for the database system.
The document provides an overview of databases and database design. It defines what a database is, what databases do, and the components of database systems and applications. It discusses the database design process, including identifying fields, tables, keys, and relationships between tables. The document also covers database modeling techniques, normalization to eliminate redundant or inefficient data storage, and functional dependencies as constraints on attribute values.
The relational database model offers a logical view of data based on relations composed of rows and columns. Relations are implemented as tables with primary keys to uniquely identify rows. Tables are linked through common attributes and operations like joins. Good design involves identifying entity relationships like one-to-one, one-to-many, and many-to-many and normalizing them.
Dbms classification according to data modelsABDUL KHALIQ
CLASSIFICATION ACCORDING TO DATA MODELS
Hierarchal Model
In a hierarchical data model, data are organized into a tree-like structure.
Network Model
based on an enlargement of the concept of hierarchical data bases.
Relational Model
Data are stored in tables
Object Oriented model
Object oriented data base systems are the most recent development in data base technology.
Introduction
Definations
Advantages and Disadvantages
PowerPoint Presentation
PowerPoint Presentation for free
Dbms architecture
Three level architecture is also called ANSI/SPARC architecture or three schema architecture
This framework is used for describing the structure of specific database systems (small systems may not support all aspects of the architecture)
In this architecture the database schemas can be defined at three levels explained in next slide
This document discusses database normalization through various normal forms. It defines key concepts like functional dependencies and full functional dependencies. It explains the objectives and rules of first, second, third normal forms and BCNF. First normal form requires each field to contain a single value. Second normal form requires fields to depend on the whole primary key. Third normal form and BCNF further eliminate transitive dependencies. The document provides examples to illustrate normalization and resolving anomalies through decomposition. It also introduces multi-valued dependencies and fourth normal form.
The document discusses different methods of organizing computer files, including heap files, sequential files, indexed-sequential files, inverted list files, and direct files. It provides details on each method, such as how records are stored and accessed, their advantages and disadvantages, and examples. Key aspects covered include unordered storage in heap files, ordered storage and efficient sequential access in sequential files, indexed access for both sequential and random access in indexed-sequential files, and direct calculation of record locations in direct files.
The document discusses key concepts related to databases and database management systems. It defines a database as a collection of organized data and a database management system as a computer program that allows for creating, accessing, managing and controlling databases. It describes three common data models - relational, network and hierarchical - and explains some fundamental database concepts like tables, keys, relations and normalization.
This document defines database and DBMS, describes their advantages over file-based systems like data independence and integrity. It explains database system components and architecture including physical and logical data models. Key aspects covered are data definition language to create schemas, data manipulation language to query data, and transaction management to handle concurrent access and recovery. It also provides a brief history of database systems and discusses database users and the critical role of database administrators.
A database administrator is responsible for installing, configuring, upgrading, administering, monitoring and maintaining databases. Key responsibilities include database design, performance and capacity issues, data replication, and table maintenance. DBAs ensure proper data organization and management through their skills in SQL, database design, and knowledge of database management systems and operating systems. There are several types of DBAs based on their specific roles like system DBA, database architect, and data warehouse administrator.
Student POST Database processing models showcase the logical s.docxorlandov3
Student POST:
Database processing models showcase the logical structure of a database. The most commonly used model is the Relational database model that sorts the data in a table that consist of rows and columns. The column holds the attributes of the entity and rows hold the data of a particular instance of the entities. The major advantage of the Relational model is that it is in the table form and hence easier for users to understand, manage and work with the data. And, with the primary key and foreign key concepts, the data can be uniquely identified, stored in different entities and retrieved effectively with the relationships. The other advantage is that with the relational model, SQL language can be used to work with the data which is simple to understand and most widely used. The disadvantage of relational model could be the financial cost that is higher in comparison as the specific software needs to be in place and the regular maintenance needs to be performed that requires highly skilled manpower. And, the complexity of the database can be further increased when the volume of the data keep in increasing. Also, there is the limitation in the length of fields stored as different data types in relational model (Joseph & Paul, 2009).
The other processing model is the Object-oriented model that depicts database as the collection of objects. The advantage of this model is that it is compatible to work with complex data sets with the use of Object IDs and object-oriented programming. It’s disadvantage is that object databases are not commonly used and the complexity can hamper the performance of database. The other type of database model is the Entity-Relationship model which is mostly used for the conceptual design of database. It pictures the entities, several attributes that falls within the domain of that entity and the cardinality of relationship between them. It’s advantage is that the E-R diagram is easily understandable by the users at the first glance and thus can effectively work with the data in no time and can point out the discrepancies in the data. The other advantage is that it can be easily converted to other models if required by the business. The disadvantage of Entity-Relationship is that the industry standard notations for the diagram is not defined and thus can create confusion to the users. This model is only suitable for high-level database design (S.J.D.,2020).
2Nd Student POST :
Database models or commonly referred to as schemas help represent the structure of a database and its format which is run by a DBMS. Database model uses vary depending on user specifications.
Types of database models
1.
Network model
This network model uses a structure similar to that of a hierarchical model. The model permits multiple parents, which is a tree-like structure model. This model emphasizes two basic concepts; records and sets. Records hold file hierarchy and sets define the many-to-many relationship .
A database model refers to the structure of a database and determines how the data within the database can be organized and manipulated. Let’s explore some common types of database models:
Relational Model: The most popular example, the relational model, organizes data into tables (also known as relations). Each table contains rows representing records and columns representing attributes. Relationships between tables are established using keys.
Hierarchical Model: Developed by IBM for IMS (Information Management System), this model arranges data in a tree-like structure. Each record is a tree node, and relationships follow a one-to-many pattern. It’s predictable and efficient for data access.
Network Model: This model allows many-to-many relationships between records. It’s more flexible than the hierarchical model but less common.
Entity–Relationship Model (ER Model): It represents entities, their attributes, and the relationships between them. ER diagrams visually depict these components.
Object Model: Used in object-oriented databases, it treats data as objects with properties and methods. It’s suitable for complex data structures.
Document Model: Commonly used in NoSQL databases, it stores data as documents (e.g., JSON or XML). Each document can have varying attributes.
Entity–Attribute–Value (EAV) Model: A flexible model where data is stored in a sparse matrix. It’s useful for handling dynamic attributes.
Star Schema: Primarily used in data warehousing, it simplifies complex data structures into a central fact table connected to dimension tables.
A data model is a set of concepts that define the structure of data in a database. The three main types of data models are the hierarchical model, network model, and relational model. The hierarchical model uses a tree structure with parent-child relationships, while the network model allows many-to-many relationships but is more complex. The relational model - which underlies most modern databases - uses tables with rows and columns to represent data, and relationships are represented by values in columns.
The document discusses different data models used in database management systems. It describes hierarchical, network, and relational data models. The hierarchical model uses a parent-child structure and pointers to link data. The network model also uses pointers but allows a many-to-many relationship between data unlike the hierarchical one-to-many structure. The relational model stores data in tables and allows flexible querying of relationships between different tables.
The document discusses different data models including hierarchical, network, and relational models. It provides details on each model such as their structure, advantages, and disadvantages. The relational model is the most popular and extensively used model. It represents data in tables with rows and columns, and defines relationships between tables using primary and foreign keys. The document also describes the basic building blocks of a relational model including entities, attributes, relationships, and constraints.
The document discusses different data models including hierarchical, network, relational, object-oriented, and object-relational models. It provides details on each model's structure and advantages and disadvantages. It also discusses using the relational model for a database to manage information for the Fly High Airlines, including passenger, payment, and seat information. The relational model is justified as the best fit due to its ability to efficiently query and join table data while ensuring data integrity.
Relational Database explanation with detail.pdf9wldv5h8n
A relational database is a type of database that stores and provides access to data points that are related to one another. Relational databases are based on the relational model, an intuitive, straightforward way of representing data in tables.A relational database is a type of database that stores and provides access to data points that are related to one another. Relational databases are based on the relational model, an intuitive, straightforward way of representing data in tables.
https://www.learntek.org/blog/types-of-databases/
Learntek is global online training provider on Big Data Analytics, Hadoop, Machine Learning, Deep Learning, IOT, AI, Cloud Technology, DEVOPS, Digital Marketing and other IT and Management courses.
This document provides an overview of different data models, including object-based models like the entity-relationship model and object-oriented model, and record-based models like the relational, network, and hierarchical models. It describes the key features of each model, such as how data and relationships are represented, and highlights some advantages and disadvantages. The presentation is intended to guide students in understanding different approaches to database design and logical data modeling.
This document provides an overview of different data models including the hierarchical model, network model, relational model, entity-relationship model, object-oriented model, object-relational model, and semi-structured model. It describes the key concepts and components of each model such as entities, attributes, relationships, as well as their advantages and disadvantages. The document is part of a lecture note on database management systems.
The document discusses database system architecture and data models. It introduces the three schema architecture which separates the conceptual, logical and internal schemas. This provides logical data independence where the conceptual schema can change without affecting external schemas or applications. It also discusses various data models like hierarchical, network, relational and object-oriented models. Key aspects of each model like structure, relationships and operations are summarized.
The document discusses several data models:
- The hierarchical model organizes data in a tree structure and only allows one-to-many relationships.
- The network model extends the hierarchical model by allowing many-to-many relationships through multiple parents.
- The relational model organizes data in tables and uses relationships maintained through common fields. It is the most widely used model.
- The entity-relationship model develops conceptual designs through entity-relationship diagrams.
- The object-oriented model contains both data and relationships within objects and allows inheritance between classes.
- The object-relational model combines features of the relational and object-oriented models.
- The semi-structured model permits different attribute
INFORMATION TECHNOLOGY PRESENTATION ON INFORMATON MANAGEMENT.pptxodane3
A flat-file database stores records in a simple file without structures for indexing or recognizing relationships between records. It has disadvantages like being harder to update and query. A relational database separates logical and physical structures and makes it easy to sort and find structured data. However, it can only store tabular data, limiting complex relationships. A hierarchical database organizes data in a tree structure with parent-child relationships. It has advantages for efficiency but rigid structure and data duplication. A network database uses a graph schema to flexibly represent object relationships but requires more complex management.
This document provides an overview of different data models, including object-based models like the entity-relationship model and object-oriented model, and record-based models like the relational, network, and hierarchical models. It describes the key features of each model, such as how data and relationships are represented, and highlights some of their advantages and disadvantages. The presentation aims to guide students in understanding different approaches to database design and modeling.
1) The document discusses different database models including hierarchical, network, and relational models. The relational model organizes data into tables and allows relationships between tables.
2) It provides examples of one-to-one, one-to-many, and many-to-many relationships.
3) The relational database management system (RDBMS) is introduced, with Oracle given as an example RDBMS. RDBMSs must satisfy E.F. Codd's 12 rules to be considered fully relational.
Chapter-2 Database System Concepts and ArchitectureKunal Anand
This document provides an overview of database management systems concepts and architecture. It discusses different data models including hierarchical, network, relational, entity-relationship, object-oriented, and object-relational models. It also describes the 3-schema architecture with external, conceptual, and internal schemas and explains components of a DBMS including users, storage and query managers. Finally, it covers database languages like DDL, DML, and interfaces like menu-based, form-based and graphical user interfaces.
The document provides an overview of database management systems (DBMS). It discusses the need for DBMS, different database architectures including centralized, client-server and distributed. It also covers data models, ER diagrams, relational models, and SQL. Key advantages of DBMS over file systems include reducing data redundancy, improving data integrity and security, and enabling concurrent access.
The document discusses various database models including flat file, hierarchical, network, relational, object-relational, and object-based models. It provides a brief history of database development, from manual files to relational databases. It describes key aspects of relational databases including how data is organized into logical tables with rows and columns.
- A data model is an abstraction that represents real-world objects and their relationships to help describe an organization's data requirements. It includes concepts for describing data, relationships between data, and constraints on the data.
- Early data models included the hierarchical and network models, which used pointers to represent physical relationships between records. This led to issues like data redundancy and an inability to easily change relationships.
- The relational model was developed to address limitations of earlier models by using logical relationships without pointers. It represented a significant improvement over previous approaches.
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How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
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2. INTRODUCTION:
DBMS Model is defined as the logical plan and arrangement of a database which
describes how the data info will be stored, retrieved and modified in a database
management system.
This DBMS Model illustrates the coherent structure of a database server that consists
of the relationships and limitations which helps to regulate how data information can be
preserved and fetched later.
Database models can be independently designed on the basis of guidelines and ideas of
whichever larger data model the creators approve.
There are different kinds of DBMS Models which matches to different phases of the
database design procedure.
3. DIFFERENT DBMS MODELS
Relational Model
Network Model
Hierarchical Model
Object-Oriented Database Model
Object Relational Model (It syndicates the two which create up its
name)
Entity-Relationship Model
Record Based DBMS Model
Document Database Model
4. Relational Model
The relational model represents DB in the form of a collection of various relations. This relation
refers to a table of various values. And every row present in the table happens to denote some real-
world entities or relationships.
It also represents how data is stored in Relational Databases. A relational database consists of a
collection of tables, each of which is assigned a unique name..
Thus, in the relational model, basically, this data is stored in the form of tables. However, this
data’s physical storage is independent of its logical organisation.
This model generates one to one, many to many and one to many relationships. The tables can be
normalized within the database by following certain rules where every piece of data is broken into
small or, say, nuclear pieces, which are beneficial.
5. Properties of a Relational Model
• Every row is unique
• All of the values present in a column hold the same data
type
• Values are atomic
• The columns sequence is not significant
• The rows sequence is not significant
• The name of every column is unique
6. Advantages
• Simplicity and Ease of Use: The relational model offers a simple and intuitive way to
organize and represent data. It uses tables with rows and columns, making it easy for
users to understand and work with the data.
• Data Independence: The relational model provides data independence, separating the
logical structure of the data (schema) from its physical storage. This allows for
flexibility in modifying the database schema without affecting the applications or
queries built on top of it.
• Flexibility and Scalability: The relational model offers great flexibility in querying and
manipulating data. It supports powerful query languages, such as SQL (Structured
Query Language), which provide rich functionalities for retrieving, updating, and
aggregating data. Additionally, relational databases can handle large amounts of data
and scale well as data volumes increase.
• Data Integrity and Consistency: The relational model enforces data integrity through
various constraints, such as primary keys, foreign keys, and unique constraints. These
constraints ensure the consistency and accuracy of data, preventing the introduction of
inconsistent or invalid records.
7. Disadvantages
• Complex Joins and Performance: When dealing with complex data relationships,
performing joins between multiple tables can become complex and computationally
expensive. Inefficient query design or lack of appropriate indexes can result in
performance issues.
• Data Redundancy: In some cases, the relational model can lead to data redundancy,
meaning the same data is stored in multiple tables. Redundancy can consume
additional storage space and increase the complexity of maintaining data consistency.
• Limited Flexibility for Unstructured Data: The relational model is primarily
designed for structured data with well-defined schemas. Handling unstructured or
semi-structured data, such as text documents or multimedia files, can be challenging
within the relational model. This has led to the rise of other database models, like
NoSQL and document databases, that better accommodate such data types.
• Impedance Mismatch: The relational model and object-oriented programming
languages often have a mismatch in their data models. Mapping objects to relational
tables (object-relational mapping) can introduce complexities and difficulties in
maintaining consistency between the two models.
8. ID_NO NAME ADDRESS ROLL_NO AGE
C1 RIYA DELHI 15 20
C2 SUNITA GURGAON 16 22
C3 ASHWANI ROHTAK 12 18
C4 PREETI DELHI 17 25
Now, let us consider a relation EMPLOYEE with attributes ID_NO, NAME, ADDRESS, ROLL_NO, and
AGE shown in this table
9. Network Model
• The network model is a database model that organizes data in a network-like
structure, allowing records to have multiple parent-child relationships. It was
developed as an extension of the hierarchical model to address its limitations.
• In the network model, data is represented as collections of records, and the
relationships between records are established using set relationships called sets.
• A set consists of a parent record type, a member record type, and a set type. The
set type defines the nature of the relationship, such as one-to-one, one-to-many,
or many-to-many.
10. key features of the network model:
• Records: Data is stored in records, which are similar to the concept of rows in the
relational model. Each record contains fields or attributes that hold specific data values.
• Sets: Sets are used to define relationships between records. A set allows a member record
to be linked to one or more parent records. This capability enables complex relationships
and allows records to have multiple paths to access related data.
• Parent-Child Relationships: In the network model, records are organized in parent-
child relationships. A parent record can have multiple child records, and a child record
can have multiple parent records.
• Access Paths: The network model provides multiple access paths to navigate through the
data. Each set in the network model is associated with a specific access path, allowing
efficient retrieval of related records.
• Data Integrity: The network model supports data integrity through the use of
constraints, such as mandatory relationships, cardinality constraints, and referential
integrity.
11. Advantages
• Flexibility in Data Relationships: The network model offers greater flexibility in
representing complex data relationships compared to the hierarchical model. It
allows for many-to-many relationships between records, enabling more diverse and
intricate connections between data elements.
• Efficient Data Access: The network model provides efficient data access by
allowing direct access to related records without the need for navigating through the
entire hierarchical structure. It utilizes set-based operations and pointers, which can
result in faster data retrieval.
• Data Integrity: Similar to the hierarchical model, the network model enforces data
integrity through referential integrity constraints. It ensures that each record has
valid connections to other related records, maintaining data consistency.
• Data Sharing and Integration: The network model supports data sharing and
integration between different applications or database systems. Records in the
network model can have multiple owners or users, enabling shared access to data
and facilitating collaboration.
12. Disadvantages
• Complexity and Learning Curve: The network model has a higher level of complexity
compared to the hierarchical and relational models. Understanding and designing a network
database can be challenging, requiring a deeper understanding of data relationships and
navigating through the network structure.
• Lack of Structural Independence: Unlike the relational model, the network model lacks
structural independence. Modifying the database schema often requires changes to the entire
network structure, which can be cumbersome and may impact existing applications and
data.
• Limited Scalability: The network model can face limitations in terms of scalability,
especially when dealing with large and evolving data structures. Adding or modifying data
relationships may require significant restructuring of the entire network, making it less
flexible and less suitable for rapidly changing data requirements.
• Data Redundancy and Complexity: The network model can suffer from data redundancy
when multiple relationships are defined between records. This redundancy can result in
increased storage requirements and complexity in maintaining data consistency and
integrity.
13. Hierarchical Model
In this model, data records are arranged into a tree-like organization,
where every record includes only a root or a parent.
The sibling records are arranged in specific in a distinct order which
is then implemented as the physical order for storing the database.
For explaining several real-world relationships, this type of model is
useful.
In the ’60s and ’70s, this model was normally implemented by
IBM’s Information Management Systems. However, due to few
functioning disorganizations, they are infrequently seen currently.
14. 1. Data Structure: Data is organized in a hierarchical structure, resembling a tree.
Each record is connected to one or more parent records and may have multiple child
records. The relationships are represented as one-to-many relationships, where each
parent can have multiple children, but each child has only one parent.
2. Parent-Child Relationships: The hierarchical model uses parent-child
relationships to represent the organization and structure of data. A parent record is
called a segment, and a child record is called a subordinate segment. The segments are
connected through pointers or links.
3. Access Paths: The hierarchical model provides predefined access paths that allow
efficient navigation through the data structure. The access paths follow the hierarchical
relationships, enabling easy traversal from parent records to child records.
Features of the Hierarchical Model model
15. 4. Data Integrity: The hierarchical model enforces data integrity through
hierarchical relationships. It ensures that each child record must have a valid
parent record and maintains referential integrity within the structure.
5. Rigidity: The hierarchical model has a rigid and inflexible structure since it
relies on predefined parent-child relationships. Any changes to the structure
require modifying the database schema and potentially impacting existing
data and applications.
6. Querying: Querying in the hierarchical model typically involves traversing
the hierarchy using predefined access paths.
Query languages specific to the hierarchical model, such as IMS DL/I (Data
Language/I), were used to retrieve data based on the hierarchical structure
16. Advantages
• Simplicity: The hierarchical model is relatively simple to understand and
implement. It follows a straightforward parent-child relationship structure, which
makes it easy to visualize and navigate the data.
• Efficient Data Retrieval: The hierarchical model provides efficient data
retrieval when accessing data in a top-down manner. Traversing the hierarchical
structure using predefined access paths allows for quick and direct access to
related records.
• Data Integrity: The hierarchical model enforces data integrity through
hierarchical relationships. Each child record must have a valid parent record,
ensuring the consistency and integrity of the data.
• Performance: The hierarchical model can offer excellent performance for
certain types of data access patterns. It is particularly efficient when the access
patterns align with the hierarchical structure, such as when retrieving all child
records of a specific parent.
17. Disadvantages
Lack of Flexibility: The hierarchical model has limited flexibility and is less adaptable to
changes in the data structure. Any modifications to the structure, such as adding or
rearranging records, require altering the database schema and potentially impacting existing
data and applications.
Complex Relationships: The hierarchical model struggles with representing complex
relationships that do not fit neatly into a strict parent-child hierarchy. Many-to-many
relationships or non-hierarchical relationships are challenging to represent effectively within
the hierarchical model.
Data Redundancy: In the hierarchical model, data redundancy can occur when multiple
child records need to refer to the same parent record. This redundancy can lead to data
inconsistency and increased storage requirements.
18. The Object-Oriented (OO) Model
• The hierarchical model is a database model that organizes data in a tree-like
structure with parent-child relationships. It was one of the earliest database
models, primarily used in early mainframe database systems like IBM's
Information Management System (IMS).
In the hierarchical model:
• Data Structure: Data is organized in a hierarchical structure, resembling a tree.
Each record is connected to one or more parent records and may have multiple
child records. The relationships are represented as one-to-many relationships,
where each parent can have multiple children, but each child has only one parent.
• Parent-Child Relationships: The hierarchical model uses parent-child
relationships to represent the organization and structure of data. A parent record is
called a segment, and a child record is called a subordinate segment. The segments
are connected through pointers or links.
19. • Access Paths: The hierarchical model provides predefined access paths that allow
efficient navigation through the data structure. The access paths follow the
hierarchical relationships, enabling easy traversal from parent records to child
records.
• Data Integrity: The hierarchical model enforces data integrity through
hierarchical relationships. It ensures that each child record must have a valid
parent record and maintains referential integrity within the structure.
• Rigidity: The hierarchical model has a rigid and inflexible structure since it relies
on predefined parent-child relationships. Any changes to the structure require
modifying the database schema and potentially impacting existing data and
applications.
• Querying: Querying in the hierarchical model typically involves traversing the
hierarchy using predefined access paths. Query languages specific to the
hierarchical model, such as IMS DL/I (Data Language/I), were used to retrieve
data based on the hierarchical structure
20. Advantages
• Modularity and Code Reusability: The OO model promotes modularity by
encapsulating data and behavior within objects. This modularity allows for code
reusability, as objects and classes can be easily reused in different parts of an
application or in different applications altogether.
• Data Abstraction and Encapsulation: The OO model provides data abstraction,
allowing complex data structures to be represented as objects with well-defined
interfaces. Encapsulation ensures that the internal details of objects are hidden,
protecting the integrity of data and providing a clear separation between the
implementation and usage of objects.
• Inheritance and Polymorphism: The OO model supports inheritance, allowing
classes to inherit attributes and methods from parent classes. Inheritance promotes
code reuse, enhances modularity, and enables the creation of hierarchical
relationships. Polymorphism, another feature of the OO model, allows objects of
different classes to be treated uniformly through common interfaces, enabling
flexible and extensible designs.
21. Disadvantages
• Performance Overhead: The object-oriented model can introduce performance
overhead compared to more low-level or procedural approaches. The abstraction
and encapsulation layers add an extra level of indirection, which can impact
performance-critical applications.
• Complexity: Object-oriented programming can sometimes lead to complex code
structures, especially when the system becomes large or when the relationships
between objects become intricate. Maintaining a clear and understandable design
becomes crucial to avoid confusion and maintain code quality.
• Learning Curve: Understanding and effectively applying the principles of the OO
model can have a steeper learning curve compared to procedural programming.
Object-oriented concepts, such as inheritance, polymorphism, and design patterns,
require additional knowledge and experience to be used effectively.