Unit I - Database Management System

Unit I - Database Management System

• Database Management System (DBMS) is software for organizing, storing, and retrieving data from a computer.
• Data is a collection of facts and figures.
• Data collection increased significantly requiring safer storage methods, leading to the development of DBMSs.
• DBMSs manage data safely and efficiently while considering security measures.
• DBMSs consist of programs to manipulate and manage the database.

Need for DBMS

• Data is collected daily and needs secure storage.
• DBMS allows organization, storage, and retrieval of data.
• DBMS acts as an interface between users and the computer's stored memory.
• DBMS considers security measures while managing data.

History of DBMS

• First DBMS was designed in 1960 by Charles Bachman.
• IBM's Information Management System (IMS) introduced in 1970.
• Entity-relationship model (ER model) developed in 1976 by Peter Chen.
• Relational Model widely adopted in 1980.
• Object-oriented databases developed in the 1980s and 1990s.
• Microsoft Access introduced as a personal DBMS in 1991, displacing others.
• Internet-based database applications emerged in 1995.
• XML integration into DBMS products started in 1997.

Characteristics of DBMS

• Provides data security and reduces redundancy.
• Self-describing database system.
• Isolates programs from data.
• Supports multiple data views.
• Allows data sharing by multiple users.
• Data manipulation software allows entities, relations, to form tables.
• ACID concept (Atomicity, Consistency, Isolation, and Durability) is adhered to.
• Supports multi-user environment for parallel data access and manipulation.

DBMS vs File

• Structure: File system manages files in a storage medium; DBMS manages a database.
• Data Redundancy: File systems can have redundant data, while DBMSs avoid it.
• Backup and Recovery: File systems lack backup/recovery if data is lost; DBMSs provide backup and recovery.
• Query Processing: DBMSs have efficient query processing, file systems do not.
• Security Constraints: File systems provide less security compared to DBMSs.
• DBMSs usually more expensive but more secure than file systems.

DBMS vs RDBMS

DBMS vs RDBMS (Continued)

Data Models

• Data modeling is the process of creating a conceptual view of the information a database contains.
• The process results in a data model defining data objects (entities) and relationships among them.

Data Models (Continued)

• The design process for a database starts with business requirements and processes.
• Raw data types from various areas are normalized.
• Primary and foreign keys define relationships for data retrieval.
• View and indexes help in finding specified data accurately and quickly

Types of DBMS

• Network
• Hierarchical
• Relational
• Object-Oriented

Relational Model

• Introduced in 1970 by C.F. Cod.
• Relates data elements using tables to avoid errors associated with repeated entries.
• Each table in relational models has at least one primary key to uniquely identify each record.
• Structured Query Language (SQL) is used for data retrieval.

Relational Model (Continued)

• Database Design Objectives: Eliminate Data Redundancy and Ensure Data Integrity.

Relational Model (Components)

• Relations/tables
• Attributes/columns
• Tuples/rows/records/entities
• Primary keys

Relational Model (Continued)

• Relationship Types: one-to-one, one-to-many, many-to-many

Network Model

• Represents complex data relationships effectively.
• Organizes entities in a graphical representation; entities can have multiple paths.
• Uses a circular linked list structure and relationships to access data quickly.

Network Model (Continued)

• Advantages: Represents complex relationships better than hierarchical models, flexible data access, and improved database performance.
• Disadvantages: Can be structurally complex and difficult to manage.

Hierarchical Model

• Represents data in a hierarchical (tree-like) structure.
• Each record has a single parent record.
• Uses explicit links between table structures leading to fast data retrieval and referential integrity enforcement.
• Can be difficult to accommodate complex relationships and require extensive changes in the case of modification.

Hierarchical Model (Continued)

• Advantages: Fast data retrieval and referential integrity.
• Disadvantages: Inability to handle complex relationships and difficult modifications.

Object-Oriented Model

• Represents real-world situations as objects with attributes and methods.
• Objects have relationships.
• Similar attributes/methods are grouped as classes.
• Objects inherit attributes from their classes.

Object-Oriented Model (Continued)

• Advantages: Easily stores complex objects with multiple relationships, supports automatic assignment of identifiers.
• Disadvantages: Object databases are not widely adopted and may be computationally expensive for certain applications.

OODBMS

• Advantages: Efficient storage and retrieval of complex data. Automatic Object IDs. Good for object-oriented languages.
• Disadvantages: OODBMS are not very common. Some complex objects may have high processing time. Language dependence exists. Few ad hoc queries.

Instance and Schema

• Instance: Current data in a database.
• Schema: Structure and organization of a database.

Three-Schema Architecture

• Three levels: external, conceptual, and internal.
• Separates user applications from physical database structure.
• External level: User views of the database.
• Conceptual level: Global view, data structures and relationships.
• Internal level: Physical storage structure of the database.

Three-Schema Architecture (Continued)

• Objective: Allows multiple users to access the same data with personalized views.
• Desirable Separation reasons: Different user needs, data change over time, internal processes don't concern users, diverse user requirements, and changes to database structure without User impact.

Three Schema (Continued)

• Internal Level: Describes the physical storage structure of the database. Uses physical storage schema and the physical data model to depict complex low-level data.
• Conceptual Level: Represents the database structure and relationships from a global perspective and hides implementation details.
• External Level: Provides different views of the database for different users or applications, hiding details of the other levels from users.

Conceptual/Internal Mapping

• Defines the correspondence between the conceptual level's records and fields and the internal level's files and structures.

External/Conceptual Mapping

• Defines the relationship between a specific external view and the global conceptual view.

Data Independence

• Logical: Changes in logical database design do not necessitate changes to user views.
• Physical: Changes in physical database design do not necessitate changes to the conceptual design.
• Occurs at the user interface level and is a significant characteristic for DBMS.

ER Data Model

• High-level data model based on entities and relationships.
• Describes data elements, relationships, and overall structure.
• Entity-relationships are portrayed as diagrams for easy representation and comprehension.

Component of ER Diagram

• Entity: Object, class, person, or place represented by rectangle.
• Attribute: Property of an entity represented by ellipses.
• Relationship: Connection between entities using a diamond symbol.

ER (continued)

• Weak Entity: An entity that depends upon another entity (called strong entity). It does not contain enough attributes to uniquely identify itself, requiring the additional specification from its parent entity. It's signified as a double rectangle in ER diagrams.

ER Diagram (continued)

• Key Attribute: (also known as primary key) Represent the main characteristics/identifiers of an entity. Represented in ER diagrams as underlined ellipses.
• Composite Attribute: Attribute composed of other attributes (e.g., 'Name' composed of 'First Name', 'Middle Name', 'Last Name'). Represented in ER diagrams with connected ellipses.
• Multivalued Attribute: Attributes having multiple values (e.g., Phone numbers.) Represented in ER diagrams as double ovals.
• Derived Attribute: Attribute calculated from other attributes (e.g., 'Age' calculated from 'Birth Date'). Represented in ER diagrams as dashed ellipses.

Relationship (continued)

• Types of Relationships: One-to-one, One-to-many, Many-to-many

Cardinality

• Describes the number of instances an entity can be involved in a relationship.
  • Example: One-to-One, One-to-Many, Many-to-Many

DBMS Language

• Data Definition Language (DDL) (creates structure of a database)
• Data Manipulation Language (DML) (manipulates data)
• Data Control Language (DCL ) (controls access to data)
• Transaction Control Language (TCL) (control transactions on a database)

Explore the fundamentals of Database Management Systems (DBMS) in this quiz, including their purpose, history, and need for secure data storage. Understand how DBMS serves as a vital interface for managing and retrieving data efficiently. Test your knowledge on key concepts and significant developments in the field of DBMS.