ST207      Half Unit
Databases

This information is for the 2025/26 session.

Course Convenor

Availability

Requisites

Additional requisites:

A computer programming course using Python, e.g. a pre-sessional course or Programming for Data Science (ST101).

The goal of this course is to cover concepts of database management systems, including relational and non-relational databases.

The topics covered will include: Relational database design; Structured Query Language (SQL) for database implementation and manipulation; Integrity constraints, triggers and database views; Concurrency control and recovery mechanisms; Multimedia and spatiotemporal databases; NoSQL databases (key-value stores, document, and graph databases; Vector databases and large language models (LLMs) applied to databases.

The course will demonstrate how various theoretical principles are implemented in practice in a database management system, such as MySQL or SQLite, and also in NoSQL, multimedia, spatiotemporal and vector database software.

15 hours of seminars and 20 hours of lectures in the Autumn Term.

This course has a reading week in Week 6 of Autumn Term.

Students are required to use their own laptops and install Python and other tools (under guidance of the teaching staff) on their laptops.

Students will be expected to produce 10 exercises in the AT.

A set of exercises will be given in each teaching week.

Essential Reading: 

• R. Elmasri and S. B. Navathe. Fundamentals of Database Systems, 7th edition (Global Edition). Pearson, 2016.
• G. Powell. Database Modeling Step-by-Step, CRC Press. Taylor & Francis, 2019.
• A. Beaulieu. Learning SQL: generate, manipulate, and retrieve data, 3rd edition. O'Reilly, 2020.
• E. Foster and S. Godbole. Database Systems: a pragmatic approach, 3rd edition. CRC Press, 2023.
• E. Sciore. Database Design and Implementation. 2nd edition. Springer, 2020.
• S. Bradshaw, E. Brazil, K. Chodorow. MongoDB: the definitive guide, 3rd edition. O’Reilly, 2019.
• I. Robinson and J. Webber and E. Eifrem. Graph Databases. 2nd edition. O’Reilly, 2015.

Additional Reading:

• P. Zhang. Practical Guide to Oracle SQL, T-SQL and MySQL, CRC Press. Taylor & Francis, 2018.
• A. Meier and M. Kaufmann. SQL & NoSQL Databases: models, languages, consistency options and architectures for big data management. Springer Vieweg, 2019.
• S. Bagui and R. Earp. Database Design using Entity-Relationship Diagrams, 3rd edition. CRC Press, 2023.
• C. Garrard. Geoprocessing with Python. Manning Publications, 2016.
• B. McClain. Python for Geospatial Data Analysis. O'Reilly, 2022.
• B. Prabhakaran. Multimedia Database Management Systems. Springer. 2012.
• J. Pan, J. Wang, and G. Li. Survey of Vector Database Management Systems. 2023. https://doi.org/10.48550/arXiv.2310.14021

Project (60%) in January

This component of assessment includes an element of group work.

Problem sets (40%) in November

Students are required to hand in solutions to 2 individual sets of exercises, each accounting for 20% of the final assessment. The group project will require solving a practical task involving database modelling and creation, data loading and utilisation (querying). The students are encouraged to work with relational and non-relational database tools, real and/or synthetic data, and design a database application that approximates a real scenario.