Database Systems



Course type
Summer Term 2022
moodle course available


Database technology is a key technology in practical and applied computer science. The central theme of this course is the modeling, construction, and use of databases.  The specific topics covered in the lecture are as follows:

  1. Introduction to Database Systems
  2. The Entity Relationship (ER) model and the Enhanced-ER (EER) model
  3. The Relational Data Model
  4. Relational Algebra and Calculus 
  5. The Structured Query Language (SQL)
  6. Advanced SQL
  7. SQL as Data Definition Language (DDL)  Data Manipulation Language (DML)
  8. Database Programming
  9. Physical Database Design 
  10. Query Processing 
  11. Query Optimization
  12. Concurrency and Recovery

After successful completion of this course, students will: 

  • have a basic understanding of modern database systems, their function and implementation,
  • be able to model databases using the ER, ERE, and relational models,
  • understand the relational algebra,
  • formulate queries over databases using SQL,
  • create and update databases using SQL,
  • understand the concepts of query processing and optimization,
  • understand the concepts of transaction and recovery,
  • communicate about the above aspects in English.
Lecture Organization

The lecture is held as a 4 SWS course:

  • Lecture sessions (2 SWS): Mondays 14.00-16.00
  • Exercises sessions (2 SWS): Thursdays 14.00-16.00

Basic knowledge of computer science (contents of the modules Computer Science 1 - Programming, Computer Engineering 1 - Computer Architecture and Distributed Systems).

Exercises on Databases (Übungen)

The exercises will start on the same week of the lecture. There will be four hands-on sessions, where the students have to bring their laptops to the exercise. 

  • Elmasri and S. B. Navathe: “Fundamentals of Database Systems”, PEARSON.
  • Kemper und A. Eieckler: „Datenbanksysteme: Eine Einführung“, Oldenbourg Verlag.

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210