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A btec computing assignment focused on designing a relational database system for a critical problem. It covers the key concepts of relational databases, including their structure, organization, and differences compared to non-relational (nosql) databases. The document also discusses the importance of entity relationship diagrams (erds) in database design. The assignment aims to demonstrate the student's ability to design a relational database system using appropriate tools and techniques. A comprehensive overview of the assignment requirements, including the learning objectives, submission details, and feedback from the tutorial lecturer.
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TUTORIAL LECTURER: Mr. Pham Son Tung WORD COUNT: 2000 STUDENT NAME: Nguyễn Phúc Anh STUDENT ID: BKC MOBILE NUMBER: 0925267737
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in order to deliver an answer, as relational datasets often do. Non-relational databases are therefore ideal for storing data that may be changed frequently or for applications that handle many different kinds of data. They can support rapidly developing applications requiring a dynamic database able to change quickly and to accommodate large amounts of complex, unstructured data. ( https://www.mongodb.com/databases/non-relational)
Relational databases Non-relational databases Data Structure and Organization Relational databases store data in a structured format using tables, rows, and columns. Each table represents a distinct entity, and each row within a table corresponds to a single instance of that entity. Columns represent the attributes of the entity, and rows contain the values of those attributes. Non-relational databases, also known as NoSQL databases, employ a variety of data models, including key-value, document, graph, and columnar. These models provide more flexibility in data organization compared to the rigid structure of relational databases. Flexibility Relational databases adhere to a defined schema, which outlines the data types, Non-relational databases typically offer a schema-less or schema-on-read approach.
constraints, and relationships between tables. This schema provides data integrity and consistency but can also limit flexibility in accommodating changes to the data structure. This flexibility allows for easier storage and modification of data without the constraints of a predefined schema. Manipulation and querying Relational databases primarily use the Structured Query Language (SQL) for data manipulation and querying. SQL provides a standardized and consistent way to interact with relational data, ensuring data integrity and consistency. Non-relational databases often employ their own proprietary query languages or APIs for data retrieval and manipulation. These languages vary depending on the specific data model and database implementation. Scalability and Performance Relational databases typically scale vertically, adding more processing power or storage capacity to existing hardware. This approach can be expensive and may not always be sufficient for handling large volumes of data. Non-relational databases are often designed for horizontal scalability, allowing for the distribution of data across multiple servers. This approach can handle large data volumes more efficiently and cost-effectively. Suitability Relational databases are well- suited for applications that require structured data with strong data integrity and consistency, such as transactional systems, customer relationship management (CRM), and enterprise resource planning (ERP). Non-relational databases excel in handling unstructured or semi-structured data, such as social media posts, user profiles, and real-time data feeds. They are also well- suited for applications that require high scalability and flexibility.
There are many type of databases each type has its own strengths and weaknesses, and the choice of database depends on the specific requirements of the application or use case. Here are some type of regularly use databases:
