WikiGalaxy
Fundamentals of Database Design
Introduction to Database Design
Database design is a foundational aspect of system design, crucial for creating efficient and scalable applications. It involves defining the structure, storage, and retrieval mechanisms of data.
Importance of Database Design
- Ensures data integrity and accuracy.
- Enhances performance and scalability.
- Facilitates easy maintenance and updates.
Core Concepts
- Normalization: Organizing data to minimize redundancy.
- ER Models: Diagrammatic representation of entities and relationships.
- Indexes: Structures that improve data retrieval speed.
Normalization
Definition
Normalization is the process of organizing data to reduce redundancy and improve data integrity. It involves dividing large tables into smaller, related tables and defining relationships between them.
Benefits
- Reduces data redundancy.
- Improves data integrity.
- Facilitates efficient data retrieval.
// Example: Normalizing a Student Table
// Original Table: Student(ID, Name, Course, Instructor)
// Normalized Tables:
// Student(ID, Name)
// Enrollment(ID, Course)
// Course(Course, Instructor)
Explanation
In this example, the original student table is divided into three tables to eliminate redundancy. Each table contains unique data that can be linked through foreign keys.
ER Models
Definition
Entity-Relationship (ER) models are used to visually represent the data and its relationships within a database. They help in designing a database at the conceptual level.
Components
- Entities: Objects or concepts represented by tables.
- Attributes: Properties or details of entities.
- Relationships: Associations between entities.
// Example: ER Model for a Library System
// Entities: Book, Member, Loan
// Attributes:
// - Book: ISBN, Title, Author
// - Member: ID, Name, MembershipDate
// - Loan: LoanID, LoanDate, ReturnDate
// Relationships:
// - Book is loaned to Member
Explanation
In this library system ER model, entities such as Book, Member, and Loan are defined with their respective attributes. The relationships between these entities describe how they interact with each other.
Indexes
Definition
Indexes are data structures that improve the speed of data retrieval operations on a database table at the cost of additional writes and storage space.
Types
- Single-column Indexes: Created on a single column of a table.
- Composite Indexes: Created on multiple columns of a table.
- Unique Indexes: Ensure that the indexed column has unique values.
// Example: Creating an Index
// SQL: CREATE INDEX idx_name ON table_name(column_name);
// Example: CREATE INDEX idx_student_name ON Student(Name);
Explanation
In this example, an index is created on the 'Name' column of the 'Student' table. This index will speed up queries that search for student names.
Data Integrity
Definition
Data integrity refers to the accuracy and consistency of data stored in a database. It is maintained through constraints, rules, and procedures.
Types
- Entity Integrity: Ensures each row in a table is unique.
- Referential Integrity: Ensures relationships between tables remain consistent.
- Domain Integrity: Ensures data in columns is valid and within a defined range.
// Example: Enforcing Referential Integrity
// SQL: ALTER TABLE ChildTable
// ADD CONSTRAINT fk_name FOREIGN KEY (column_name) REFERENCES ParentTable(column_name);
// Example: ALTER TABLE Orders
// ADD CONSTRAINT fk_customer_id FOREIGN KEY (CustomerID) REFERENCES Customers(ID);
Explanation
In this example, a foreign key constraint is added to the 'Orders' table to ensure that every 'CustomerID' in the 'Orders' table corresponds to an existing 'ID' in the 'Customers' table, maintaining referential integrity.
Scalability Considerations
Definition
Scalability in database design refers to the ability of a database to handle increasing amounts of data and users without compromising performance.
Strategies
- Vertical Scaling: Adding more resources to a single server.
- Horizontal Scaling: Adding more servers to distribute the load.
- Partitioning: Dividing a database into smaller, more manageable pieces.
// Example: Horizontal Scaling with Sharding
// Separate data into shards based on a key, such as user ID.
// Each shard is stored on a different server, distributing the load.
Explanation
In this example, horizontal scaling is achieved through sharding, where data is distributed across multiple servers based on a shard key. This allows the system to handle more users and data efficiently.
Backup and Recovery
Definition
Backup and recovery are processes that ensure data is protected against loss or corruption and can be restored to a previous state if necessary.
Techniques
- Full Backup: A complete copy of the entire database.
- Incremental Backup: Copies only the data that has changed since the last backup.
- Point-in-Time Recovery: Restores the database to a specific point in time.
// Example: Scheduling Regular Backups
// Use a cron job to automate daily backups.
// Example: 0 2 * * * /usr/bin/backup-script.sh
Explanation
In this example, a cron job is set up to automate daily backups of the database. This ensures that data is regularly backed up and can be restored in case of data loss.
Security Considerations
Definition
Database security involves protecting the database from unauthorized access, misuse, or malicious attacks.
Measures
- Authentication: Verifying the identity of users accessing the database.
- Authorization: Granting permissions to users based on their roles.
- Encryption: Securing data by converting it into a coded format.
// Example: Implementing Authentication
// Use a secure password policy and two-factor authentication.
// Example: ALTER USER 'username' IDENTIFIED BY 'secure_password';
Explanation
In this example, a secure password policy is enforced, and two-factor authentication is implemented to enhance the security of the database.
