Course details
Advanced Database Systems
PDB Acad. year 2020/2021 Winter semester 5 credits
The course offers broader introduction into the following modern database systems: various kinds of NoSQL databases, NewSQL databases, temporal databases, distributed databases, and advanced relational databases. There are also discussed principles of the modern database systems, their scheme, and techniques for efficient usage of such systems. In the lectures, there are also introduced implementation principles of the modern database systems and data manipulation techniques.
Guarantor
Course coordinator
Language of instruction
Completion
Time span
- 26 hrs lectures
- 6 hrs exercises
- 6 hrs pc labs
- 14 hrs projects
Assessment points
- 60 pts final exam (written part)
- 20 pts mid-term test (written part)
- 20 pts projects
Department
Lecturer
Instructor
Course Web Pages
Subject specific learning outcomes and competences
Students will be able identify clearly post-relational DB systems and, for selected categories, they will also be able to discuss issues of implementation and usage of such systems.
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Student learns terminology in Czech and English language
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Student improves in participation on a small project as a member of a small team
Learning objectives
The aim of course is to give a broader introduction into post-relational database systems (various kinds of NoSQL, NewSQL, temporal, and distributed DB). Various systems and their implementation techniques are discussed.
Why is the course taught
Number of worldwide data resources is increasing, data kinds stored in databases increases too, ways of data manipulation should change as well. Thus, this course offers introduction and deeper insight into various kinds of database management systems.
Prerequisite knowledge and skills
Fundamentals of the relational model. Normalization-based design of a relational database. Organization of data at an internal level. Data security and integrity. Transactions. Relational database design from a conceptual model. SQL language. Spatial, object-relational, and XML databases. Algorithms used for indexing in spatial databases.
Study literature
- Lecture materials (slides, scripts, etc.)
- Lemahieu, W., Broucke, S., Baesens, B.: Principles of Database Management. Cambridge University Press. 2018, 780 p.
- Kim, W. (ed.): Modern Database Systems, ACM Press, 1995, ISBN 0-201-59098-0
- Perkins, L., Redmond, E., Wilson, J.: Seven databases in seven weeks: a guide to modern databases and the NoSQL movement. Second edition. Pragmatic Bookshelf, 2018. ISBN 978-1-68050-253-4
- Dunckley, L.: Multimedia Databases: An Object-Relational Approach. Pearson Education, 2003, p. 464, ISBN 0-201-78899-3
- Gaede, V., Günther, O.: Multidimensional Access Methods, ACM Computing Surveys, Vol. 30, No. 2, 1998, pp. 170-231.
Syllabus of lectures
- Introduction, post-relational database definition, recap (O-R, multimedia, XML, spatial DB)
- NoSQL DB - column DB and their indexing, graph DB
- NoSQL DB - key-value DB, time series
- NoSQL DB - data aggregation, data warehouses
- NewSQL DB
- Column relational DB, comparison with classical storage
- Mid-term exam
- Temporal database systems, introduction
- Temporal data models
- Algorithms used in temporal database systems
- Distributed databases I
- Distributed databases II
- Conclusion, comparison of various database systems, open items discussion, another DBMS (deductive, object, ...)
Syllabus of numerical exercises
- Demonstration: introduction to NoSQL DB, column NoSQL DB, DB key-value.
- Demonstration: No SQL DB + cloud - CQRS.
- Demonstration: temporal databases - introduction to temporal databases, languages (A)TSQL2, interpreters TimeDB2, TSQL2lib, (A)TSQL2 implementation.
Syllabus of computer exercises
- Introductory computer exercise and NoSQL databases - introduction to work with particular types of NoSQL databases, indexing in such databases (column DB, key-value DB)
- NoSQL databases in a cloud - DBMS CQRS, work within cloud, exploitation of DB inside cloud
- Temporal databases - introduction to languages (A)TSQL2 as a temporal DML/DDL, queries over temporal data via (A)TSQL2
- Project demonstration
Syllabus - others, projects and individual work of students
- Design and implementation of database system for particular scalable application exploiting features of CQRS (Command and Query Responsibility Segregation). Thus, operations over data are primarily performed via relational database and reading of the data is performed via scalable NoSQL database.
Progress assessment
- Mid-term exam, for which there is only one schedule and, thus, there is no possibility to have another trial.
- One project should be solved and delivered in a given date during a term.
Exam prerequisites:
At the end of a term, a student should have at least 50% of points that he or she could obtain during the term; that means at least 20 points out of 40.
Plagiarism and not allowed cooperation will cause that involved students are not classified and disciplinary action can be initiated.
Controlled instruction
- Mid-term exam - written form, questions, where answers are given in full sentences, no possibility to have a second/alternative trial. (20 points)
- Projects realization - 1 project (program development according to a given specification) with appropriate documentation. (20 points)
- Final exam is performed in written form. Students are given questions, where answers are provided in full sentences. The maximal amount of points one can get is 60 points - the minimal number of points which must be obtained from the final exam is 25, otherwise, no points will be assigned to a student. The exam has one regular and two corrective periods. Regular period is always performed in fully written way only. Corrective periods can be performed either in fully written form or in a combined form (both written and verbal performance in a single day, written in the morning verbal in the afternoon). The form of corrective periods is announced as soon as the previous period is evaluated, while the combined form will be performed in the case when for the particular period is assigned no more than 16 students.
Exam prerequisites
At the end of a term, a student should have at least 50% of points that he or she could obtain during the term; that means at least 20 points out of 40.
Plagiarism and not allowed cooperation will cause that involved students are not classified and disciplinary action can be initiated.
Course inclusion in study plans
- Programme IT-MGR-2, field MBI, MGM, MIS, 1st year of study, Compulsory
- Programme IT-MGR-2, field MBS, MMM, MPV, any year of study, Elective
- Programme IT-MGR-2, field MIN, any year of study, Compulsory-Elective group S
- Programme IT-MGR-2, field MMI, any year of study, Compulsory-Elective group O
- Programme IT-MGR-2, field MSK, 1st year of study, Compulsory-Elective group N
- Programme MITAI, field NADE, NBIO, NCPS, NEMB, NGRI, NHPC, NIDE, NISY, NMAL, NMAT, NNET, NSEC, NSEN, NSPE, NVER, NVIZ, any year of study, Elective
- Programme MITAI, field NISD, 2nd year of study, Compulsory