Advanced Databases

Data is displayed for academic year: 2023./2024.

Laboratory exercises

Course Description

Fullt-text search in relational databases, advanced use of SQL, object and object relational databases, geospatial databases, temporal databases, NoSQL databases, semantic web and data streams.

Study Programmes

University graduate
[FER3-EN] Control Systems and Robotics - profile
Elective course (3. semester)
Elective courses (1. semester)
[FER3-EN] Data Science - profile
Elective courses (1. semester)
Recommended elective courses (3. semester)
[FER3-EN] Electrical Power Engineering - profile
Elective courses (1. semester) (3. semester)

Learning Outcomes

  1. design object-relational, temporal, spatial and NoSQL databases
  2. use object-relational, temporal, spatial, stream and NoSQL databases
  3. explain the concepts of different data models

Forms of Teaching


Students are presented with theoretical settings of selected topics intertwined with a multitude of practical examples.

Partial e-learning

Students have access to online tutorials designed to learn and master practical tasks.

Independent assignments

We encourage students to learn continuously by solving homework through a customized online platform and by creating several smaller projects in which they apply the knowledge acquired in the course.


Students discuss their own solutions to project tasks with subject teachers.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Homeworks 40 % 10 % 40 % 10 %
Seminar/Project 50 % 45 % 50 % 45 %
2. Mid Term Exam: Written 0 % 20 % 0 %
Final Exam: Written 30 % 25 %
Exam: Written 50 % 45 %

Week by Week Schedule

  1. Principles of data modeling, Window functions, recursion, pivoting
  2. Window functions, recursion, pivoting, Project
  3. text search in relational database management system
  4. Object-oriented models, Object and object-relational databases
  5. Modelling spatial and temporal data, Spatial, temportal and spatio-temporal database basics
  6. Modelling spatial and temporal data, Spatial, temportal and spatio-temporal database basics, Project
  7. Distributed DBMS
  8. Midterm exam
  9. Key value, graph, column family, document, Semi-structured data model (expressed using XML, XML Schema, JSON), NoSQL databases
  10. Graph databases, Data replication and consistency models, The impact of indices on query performance, In-memory databases
  11. NoSQL databases, Graph databases, Big data concepts, Project
  12. Systems supporting structured and/or stream content, Stream databases
  13. Data modeling for Semantic Web (RDF, OWL)
  14. Data warehouse
  15. Final exam


(.), Pramod J. Sadalage, Martin Fowler: NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence,
(.), Tyler Akidau, Slava Chernyak, Reuven Lax: Streaming Systems,

For students


ID 222946
  Winter semester
L2 English Level
L2 e-Learning
30 Lectures
0 Seminar
0 Exercises
15 Laboratory exercises
0 Project laboratory
0 Physical education excercises

Grading System

87.5 Excellent
75 Very Good
62.5 Good
50 Sufficient