PA195 NoSQL Databases

Faculty of Informatics
Autumn 2024
Extent and Intensity
2/1/0. 3 credit(s) (plus extra credits for completion). Type of Completion: k (colloquium).
In-person direct teaching
Teacher(s)
doc. RNDr. Vlastislav Dohnal, Ph.D. (lecturer)
Mgr. Luděk Bártek, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Vlastislav Dohnal, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics
Timetable
Mon 23. 9. to Mon 9. 12. Mon 10:00–11:50 D3
  • Timetable of Seminar Groups:
PA195/01: Wed 2. 10. to Wed 11. 12. each even Wednesday 10:00–11:50 B011, L. Bártek
PA195/02: Wed 25. 9. to Wed 18. 12. each odd Wednesday 10:00–11:50 B011, L. Bártek
PA195/03: Tue 1. 10. to Tue 10. 12. each even Tuesday 12:00–13:50 B011, L. Bártek
Prerequisites
PB154 Database Systems || PB168 Introduction to DB and IS
Ability to log in to Linux PCs in the faculty's computer room, and be able to operate text "terminal".
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 40 student(s).
Current registration and enrolment status: enrolled: 43/40, only registered: 6/40, only registered with preference (fields directly associated with the programme): 1/40
fields of study / plans the course is directly associated with
there are 10 fields of study the course is directly associated with, display
Course objectives
The course covers: 1) the principles behind the NoSQL databases, such as chapters from modern distributed database theory, P2P indexing or the MapReduce programming model; 2) architectures and common features of the main types of NoSQL databases (key-value stores, document databases, column-family stores, graph databases); 3) detailed description of selected NoSQL database systems including practical experience; 4) other topics related to Big Data and non-relational databases (data analytics, DB in web browser, influence of NoSQL to relational databases, etc.)
Learning outcomes
After the course, students will:
- understand the principles behind the NoSQL databases;
- know architectures and common features of the main types of NoSQL databases (key-value stores, document databases, column-family stores, graph databases);
- know in detail several selected NoSQL database systems including practical experience;
- know about other topics related to Big Data and non-relational databases (data analytics, DB in web browser, influence of NoSQL to relational databases, etc.)
Syllabus
  • Why NoSQL, Principles, Taxonomy.
  • Distribution Models, Consistency in Distributed Databases.
  • MapReduce + Hadoop.
  • Key-Value Stores, practical experience with Riak & Infinispan.
  • Document Databases, practical experience with MongoDB & PostgreSQL.
  • Column-family Stores, practical experience with Cassandra.
  • Graph Databases, practical experience with Neo4J.
  • Other topics related to Big Data and non-relational databases (data analytics, DB in web browser, influence of NoSQL to relational databases, etc.).
Literature
    recommended literature
  • HOLUBOVÁ, Irena, Jiří KOSEK, Karel MINAŘÍK and David NOVÁK. Big Data a NoSQL databáze (Big Data and NoSQL Databases). Praha: Grada Publishing, a.s., 2015, 288 pp. Profesionál. ISBN 978-80-247-5466-6. stránka nakladatele info
  • SADALAGE, Pramod J. and Martin FOWLER. NoSQL distilled : a brief guide to the emerging world of polyglot persistence. Upper Saddle River: Addison-Wesley, 2013, xix, 164. ISBN 9780321826626. info
Teaching methods
Two-hour lectures every week + bi-weekly two-hour practices in the computer room. One or two lectures will be given by external experts about their experience with NoSQL database technologies. There are five self-paced tutorials to obtain practical experience. During the seminars, there are specific assignment to solve in small teams The course is given in English.
Assessment methods
Requirements for successful completion are attendance at the seminars and completion of all assignments done in seminars.
Language of instruction
English
Further Comments
Study Materials
The course is taught annually.
Teacher's information
https://is.muni.cz/predmety/predmet.pl?kod=PA195&fakulta=1433&lang=en
The course is also listed under the following terms Autumn 2014, Spring 2016, Spring 2017, Spring 2018, Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.
  • Enrolment Statistics (recent)
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