2026/2027

A course on database systems technology providing a bottom-up perspective of database administration, based on the assumption that solid knowledge of the main performance, reliability, and scale challenges in data management allows administrators to diagnose problems, formulate testable hypotheses, and apply creative solutions in a variety of current data management systems.

This approach contrasts with the common but limiting view of database administration as the repetitive application of recipes prescribed for a specific system. Therefore, this course addresses the concerns of database administrators facing a growing diversity of tools, but also application developers and integrators where data management is their greatest challenge.

Learning outcomes

Explain the main performance, reliability, and scale challenges in data management systems.
Describe query processing and transactional mechanisms in database management systems.
Plan and apply data management solutions that combine, compose, and configure data management mechanisms.
Estimate and assess the behavior of data management systems.

Instructors

Grading

The grade has two components:

Group project (50%), with discussion required for grades over 16/20.
Written exam (50%), with at least 8/20.

The default project is the assessment and tuning of a hybrid transactional analytical application in a cloud environment in groups of 4 students. As an option, a limited set of research and development projects will be proposed for groups of 2 students.

Submitted projects must be fully authored by the students and must not contain materials (text, code, …) from third parties, obtained online, or using AI tools unless explicitly marked and authorized by the instructors. See Academic Regulations and Code of Ethical Conduct for more information.

Schedule

#	Date	Topic	Mat.	Read
T1	24/9/26	Introduction.	pdf	B2
PL1		Lab 0: Benchmark.	pdf zip
T1	1/10/26	Physical representation.	pdf	B1 13
PL2		Lab 1: Resources.	pdf zip
T3	8/10/26	Physical operators.	pdf	B1 15
PL3		Lab 2: Execution.	pdf zip
T4	15/10/25	Redundancy.	pdf demo	B1 8,14
PL4		Lab 3: Redundancy.	pdf zip

Bibliography

#	Title
B1	H. Garcia-Molina, J. Ullman and J. Widom. Database Systems: The Complete Book. Prentice-Hall, 2006 (2nd Edition).
B2	J. M. Hellerstein, M. Stonebraker, and J. Hamilton. Architecture of a Database System Foundations and Trends® in Databases, vol. 1, no. 2, pp. 141–259, 2007.
B3	B. Ding, V. R. Narasayya, and S. Chaudhuri, Extensible Query Optimizers in Practice. Foundations and Trends® in Databases, 2024.
B4	J. Gray and A. Reuter. Transaction processing: Concepts and techniques. Morgan-Kaufmann, 1993.
P1	M. Stonebraker and A. Pavlo. What Goes Around Comes Around… And Around SIGMOD Record, vol. 53, no. 2, p. 21, 2024.
P2	T. Kersten, V. Leis, A. Kemper, T. Neumann, A. Pavlo, and P. Boncz, Everything you always wanted to know about compiled and vectorized queries but were afraid to ask. In Proceedings VLDB Endowment, vol. 11, no. 13, pp. 2209–2222, Jan. 2019.
P3	V. Leis, A. Gubichev, A. Mirchev, P. Boncz, A. Kemper, and T. Neumann, How good are query optimizers, really?, Proceedings VLDB Endowment, vol. 9, no. 3, pp. 204–215, Nov. 2015.
P4	A. Prout et al., Cloud-Native Transactions and Analytics in SingleStore. In Proceedings of the 2022 International Conference on Management of Data, SIGMOD’22, 2022.

Past editions

Google Cloud Credits Link

https://docs.google.com/spreadsheets/d/1yoNJEWmqPgq5GT7WgW3w-rTjDoEH4WK4f6Mb5Zqpyo4/edit?usp=sharing