DATABASE

Database

What is Data?

Data refers to a collection of discrete units of information. It can take various forms, including text, numbers, media, and bytes, and can be stored on paper or in electronic memory, among other formats.

The term 'data' originates from the Latin word 'datum,' which means 'a single piece of information.' As the plural of 'datum,' 'data' represents multiple pieces of information.

In computing, data is information that can be converted into a format suitable for efficient processing and transfer. Data is versatile and can be interchanged across different systems and applications.

What is a Database?

• A database is an organized collection of data designed for easy access and management. 
• Data within a database is typically structured into tables, rows, and columns, and indexed to facilitate quick retrieval of relevant information. 
• Databases are created and managed by software programs that ensure all users can access the data through a single, cohesive system.
• The primary purpose of a database is to handle large volumes of information by storing, retrieving, and managing data efficiently.
• Many dynamic websites on the World Wide Web rely on databases. For instance, a hotel booking system that checks room availability is an example of a dynamic site that utilizes a database.
• Popular databases include MySQL, Sybase, Oracle, MongoDB, Informix, PostgreSQL, and SQL Server.
• Modern databases are typically managed by a Database Management System (DBMS), which oversees their operation and functionality.

SQL, or Structured Query Language, is utilized to manage and manipulate data within a database. It is based on principles from relational algebra and tuple relational calculus.

A cylindrical structure is employed to visually represent a database's image.

Evolution of Databases

Databases have undergone significant transformation over the past 50 years, evolving from simple flat-file systems to sophisticated relational and object-relational systems. This evolution can be categorized into several generations:

 File-Based Systems

Introduced in 1968, file-based databases stored data in flat files. While they offered various advantages, such as multiple access methods (sequential, indexed, and random), they also had notable limitations. Managing data in file-based systems required extensive programming in third-generation languages like COBOL and BASIC.

Hierarchical Data Model

From 1968 to 1980, the Hierarchical Data Model became prominent. One of the most notable hierarchical databases from this era was IBM's IMS (Information Management System), which represented a significant advancement in database management systems.
The diagram below illustrates the Hierarchical Data Model. In this model, small circles represent objects.

Similar to file systems, the Hierarchical Data Model had several limitations. These included complex implementation, a lack of structural independence, and difficulty in handling many-to-many relationships, among others.

Network Data Model

The first DBMS using the Network Data Model was developed by Charles Bachman at Honeywell and was known as Integrated Data Store (IDS). Although it was created in the early 1960s, it was standardized in 1971 by the CODASYL group (Conference on Data Systems Languages).

In this model, files are organized in a network structure where they are related as owners and members, resembling the common network model.

The Network Data Model identifies the following components:

1. Network Schema: Defines the overall organization of the database.
2. Sub-Schema: Provides specific views of the database tailored for individual users.
3. Data Management Language: A procedural language used for managing data within the model.

Cloud Database

A cloud database allows you to store, manage, and retrieve both structured and unstructured data through a cloud platform. This data is accessible via the Internet. Often referred to as Database as a Service (DBaaS), cloud databases are provided as managed services.

These databases adhere to the principles of object-oriented programming, making them a hybrid application. The object-oriented database model is characterized by the following properties:

Some top cloud database options include:

• AWS (Amazon Web Services)
• Snowflake Computing
• Oracle Database Cloud Services
• Microsoft SQL Server
• Google Cloud Spanner

Object-Oriented Databases

Object-oriented databases store data in the form of objects and classes. In this model, objects represent real-world entities, while classes are collections of these objects. Combining features of the relational model with object-oriented principles, object-oriented databases offer an alternative to traditional relational databases.

These databases adhere to the principles of object-oriented programming, making them a hybrid application. The object-oriented database model is characterized by the following properties:

 Object-Oriented Programming Properties

Objects: Represent real-world entities with both state and behavior.
Inheritance: Allows classes to inherit attributes and methods from other classes, promoting reuse and hierarchy.

Polymorphism: Enables methods to perform different functions based on the object that is calling them.

Encapsulation: Encases data and methods within classes to protect and control access.

Relational Database Properties

Consistency: Guarantees that database transactions maintain data integrity and follow predefined rules.

Integrity: Maintains the accuracy and reliability of data within the database.

Durability: Assures that once a transaction is committed, it remains permanent even in case of system failures.

Concurrency: Manages simultaneous operations without conflicting, ensuring accurate results.

Query Processing: Involves the efficient execution of queries to retrieve and manipulate data.

 Graph Databases

A graph database is a type of NoSQL database designed to represent data using a graph structure. It consists of nodes and edges, where each node represents an entity and each edge represents a relationship between two nodes. Every node in a graph database has a unique identifier.

Graph databases excel at revealing and exploring relationships between data, making them highly effective for querying interconnected information.

These databases are particularly useful for managing complex relationships and dynamic schemas. They are commonly used in applications such as supply chain management and identifying sources in IP telephony.

 Database Management System (DBMS)

A Database Management System (DBMS) is software designed to store, manage, and retrieve data within a database. Examples of popular DBMS tools include Oracle and MySQL.

Key functions of a DBMS include:

• Interface for Operations: It provides an interface for performing various operations such as creating, deleting, and modifying databases.
• Custom Database Creation: Users can create and configure databases according to their specific needs.
• Request Handling: It processes requests from applications and retrieves the required data through the operating system.
• Program Management: A DBMS consists of a suite of programs that execute based on user instructions.
• Data Security: It ensures the security and protection of the database.

Advantages of DBMS

1. Data Integrity and Accuracy: DBMS ensures that data is accurate and consistent by enforcing data integrity constraints and rules.

2. Data Security: It provides robust security features, such as access controls and authentication, to protect sensitive information from unauthorized access.

3.Efficient Data Management: DBMS allows for efficient data storage, retrieval, and manipulation through structured query languages and optimized indexing.

4. Reduced Data Redundancy: By centralizing data management, DBMS minimizes data duplication and redundancy, leading to more streamlined data storage.

5. Concurrent Access: DBMS supports multiple users accessing and modifying data simultaneously, with mechanisms to handle conflicts and maintain data consistency.

Disadvantages of DBMS

1. Cost: Implementing and maintaining a DBMS can be expensive due to licensing fees, hardware requirements, and the need for skilled personnel.

2. Complexity: The setup and management of a DBMS can be complex, requiring specialized knowledge and training.

3.Performance Overhead: The abstraction and overhead introduced by DBMS systems can lead to performance issues, especially with large volumes of data and complex queries.

4. Backup and Recovery: Managing backup and recovery processes can be challenging and resource-intensive, particularly for large databases.

5. Security Risks: While DBMS provides security features, they also present potential security risks, such as vulnerabilities to hacking or unauthorized access if not properly configured.