Definition of a Database
A database is a structured collection of data that is stored and accessed electronically. Databases are designed to manage large volumes of information and enable efficient data retrieval, manipulation, and management.
Key Concepts in Database Fundamentals
1. Data:
Raw facts and figures without context. For example, numbers, dates, and strings.
2. Database Management System (DBMS):
Software that interacts with end-users, applications, and the database itself to capture and analyze data. Examples include MySQL, PostgreSQL, Oracle, and MongoDB.
3. Tables:
The basic storage units in a relational database. Tables consist of rows and columns, where rows represent records and columns represent attributes.
4. Records (Rows):
Individual entries in a table, represent a single instance of the data entity described by the table.
5. Fields (Columns):
Attributes or properties of the data entity. Each column in a table represents a specific type of data.
6. Primary Key:
A unique identifier for a record in a table. It ensures that each record can be uniquely identified.
7. Foreign Key:
A field in one table that uniquely identifies a row of another table. It is used to establish and enforce a link between the data in the two tables.
8. SQL (Structured Query Language):
A standardized language for managing and manipulating databases. SQL is used to perform tasks such as querying data, updating records, and managing database structures.
9. Normalization:
The process of organizing data to reduce redundancy and improve data integrity. It involves dividing a database into two or more tables and defining relationships between the tables.
10. Transactions:
A sequence of operations performed as a single logical unit of work. Transactions ensure data integrity and are characterized by ACID properties (Atomicity, Consistency, Isolation, Durability).
11. Indexes:
Data structures that improve the speed of data retrieval operations on a database table. Indexes are used to quickly locate data without having to search every row in a database.
12. Views:
Virtual tables are created by querying one or more tables. Views do not store data themselves but display data stored in other tables.
13. Schemas:
Organizational structures that define the layout of the database. Schemas include definitions of tables, views, indexes, and the relationships between them.
Characteristics of Databases
1. Data Integrity: Ensures accuracy and consistency of data over its lifecycle.
2. Data Security: Protects data from unauthorized access and breaches.
3. Data Redundancy: Minimizes duplicate data to ensure efficient storage.
4. Data Independence: Separation of data from application programs that use the data.
5. Data Consistency: Ensures that data remains accurate and consistent across the database.
6. Multi-User Access: Supports concurrent access by multiple users.
Database Management System (DBMS)
A DBMS provides several essential services to manage databases:
1. Data Definition:
– Allows the creation, modification, and removal of definitions that define the organization of the data.
2. Data Update:
– Facilitates the insertion, modification, and deletion of the actual data in the database.
3. Data Retrieval:
– Provides querying capabilities to retrieve data based on specific criteria.
4. User Administration:
– Manages user access, roles, and security.
5. Backup and Recovery:
– Ensures data is backed up regularly and can be recovered in case of data loss.
6. Concurrency Control:
– Manages simultaneous data access to ensure data integrity and consistency.
7. Data Integrity Management:
– Enforces rules to maintain data accuracy and consistency.
Types of Database Models
1. Hierarchical Model:
– Organizes data in a tree-like structure. Each record has a single parent and potentially many children. Example: IBM Information Management System (IMS).
2. Network Model:
– More flexible than the hierarchical model. Records are organized in a graph, allowing many-to-many relationships.
3. Relational Model:
– Uses tables (relations) to represent data and their relationships. Data can be accessed without reorganizing the tables. Example: MySQL, PostgreSQL.
4. Object-Oriented Model:
– Integrates object-oriented programming principles. Data is stored as objects, similar to object-oriented programming. Example: ObjectDB.
5. Document Model:
– Stores data as documents, typically in JSON or XML format. Example: MongoDB.
6. Key-Value Model:
– A simple model where each item is stored as a key-value pair. Example: Redis.
7. Column-Family Model:
– Stores data in columns rather than rows, which is ideal for analytical queries. Example: Apache Cassandra.
8. Graph Model:
– Represents data as nodes and edges, making it suitable for data with complex relationships. Example: Neo4j.
Objective: These fundamental concepts and characteristics, along with the services provided by a DBMS and the different types of database models, are crucial for effectively designing, implementing, and managing databases in various applications.
