Module 8.2- Database Concepts & Structures

Question 1

Types of Databases

Answer 1

• databases can be categorised into two broad groups: relational and non-relational databases
• each type is designed to handle specific kinds of data and relationships between data points
• understanding the differences between these databases helps determine which type is best suited for different use cases

Question 2

Relational Databases (SQL)

Answer 2

• most common type in business environments
• store data in tables with rows and columns, similar to a spreadsheet, but with much more structure and rigor

Key Features:
- they organise data into relationships using keys; this is where the name relational comes from

• Tables- data is stored in tables, where each row represents a record and each column represents a field
• Relationships- tables are linked together by primary keys (unique identifiers for each record) and foreign keys (used to connect related data across tables)

Question 3

Examples of Relational Databases

Answer 3

• Microsoft SQL
• MySQL
• PostgreSQL
• Oracle
• e.g. in an e-commerce system, you might have one table for customers and another for orders- these tables are linked by a customer ID that appears as a primary key in the customer table and as a foreign key in the orders table

Question 4

Non-Relational Databases (NoSQL)

Answer 4

• these databases don’t use predefined tables
• instead, they offer flexible data models, making them ideal for large amounts of unstructured or semi-structured data, such as documents or social
• Flexible Schema- non-relational databases can store different kinds of data without requiring a fixed table structure
• Scalability- these databases are often designed to scale horizontally, meaning they can handle large volumes of data by spreading it across multiple servers

Question 5

Examples of Non-Relational Databases

Answer 5

• MongoDB
• Cassandra
• Amazon
• DynamoDB
• a non-relational database like MongoDB stores data as JSON-like documents, ideal for applications with evolving or variable data structures

Question 6

Key-Value Databases

Answer 6

• specific type of non-relational database
• this type of database stores data as pairs of keys and values
• Simple Structure- each entry in a key-value database is a pair, with a unique key used to retrieve a specific value
• Speed and Efficiency- since these databases are optimised for fast lookups, they are often used in scenarios where performance is critical, like caching or session management

Question 7

Examples of Key-Value Databases

Answer 7

• Redis
• Amazon
• DynamoDB
• e.g. in an online store, a key-value database could be used to store and quickly retrieve the price of a product based on its product ID

Question 8

Document Databases

Answer 8

• another important type of non-relational database
• these databases store data in the form of documents, often using JSON or XML formats
• great for handling unstructured or semi-structured data, where the data fields can vary from one document to another

Question 9

What makes Document Databases stand out?

Answer 9

• Schema Flexibility- documents can vary in structure, making it easy to store diverse types of data without needing predefined schemas
• Hierarchical Data Representation- documents can store nested data, allowing you to capture complex relationships within a single document
• MongoDB
• Couchbase
• e.g. a document database might store a user profile, including their name, email, address, and even purchase history, all within a single document; this flexibility makes it ideal for applications like content management systems or product catalogs

Question 10

Relational Database Structure

Answer 10

• Tables- as mentioned earlier, data is stored in tables where each row is a record, and each column is a field that describes the data
• Primary and Foreign Keys- these are used to link tables together, ensuring that data is properly related and organised

Question 11

Non-Relational Database Structure

Answer 11

• Collections and Documents- in document databases, data is stored in collections, which are made up of documents
• each document can have a unique structure, allowing for greater flexibility in how data is organised
• Key-Value Pairs- in key-value databases, data is stored as pairs, where a key is associated with a specific value