INFO-H-415: Advanced Databases

Last important announcement

All VUB student registered to the course who are not on the Teams of the course should take contact with Once added to the Teams, please, register to the notifications of the channel to be sure not to miss any info.

Here are a few additional notes and reminders about today's exercise session.

The exercise session will start at 14h10 in UB4.126. Please arrive a bit in advance in order to have time to find a spot before the start of the recap, especially if you need to use the computer of the room (see more details about these computers further).

I will try to record the session as I have been informed that some of you have a schedule conflict. I do not guarantee that it will always work tough, I might forget or there might be some technical problems. These recordings will be available on Teams only.

I hope most of you succeeded at installing the necessary software. If it is not the case you can use the ones in the room. I tested the ones in the room Monday morning and here are some observations:

- You need to start the computer on windows. When selecting windows in the Grub, some computers get stuck on a black screen. If this is the case you need to force restart. Trying again should solve the problem on most computers. For some of them however it doesn't work. If you have the problem more than 3 time I would advise you to change the computer.

- Once you arrive on the login page, please login with you netid and password. If you do not have one you can try with fsa-vub-students as login and password (it is not guaranteed that it works, I forgot to test it). Once you entered the correct login and password you might get stuck on a loading page indicating “Please wait for the user profile service”. This takes a lot of time (took around 10 min for me) windows should finally open after so please be patient.

The system admin made an update which might have solved these problems but I couldn't test since…

See this afternoon,



Teaching Assistant


  • Theory 24 h - Exercises 24h - Project 12h
  • 5 ECTS credits

Study Programme

  • Master in Computer Science and Engineering [MA-IRIF]
  • Master in Computer Sciences [INFO]
  • Erasmus Mundus Master in Big Data Management and Analytics (BDMA)


The course is given during the first semester

  • Lectures on Mondays from 4 pm to 6 pm in the K.4.601 (Solbosch campus)
  • Exercises on Thursdays from 2 pm to 4 pm


Today, databases are moving away from typical management applications, and address new application areas. For this, databases must consider (1) recent developments in computer technology, as the object paradigm and distribution, and (2) management of new data types such as spatial or temporal data. This course introduces the concepts and techniques of some innovative database applications.


Active Databases

Taxonomy of concepts. Applications of active databases: integrity maintenance, derived data, replication. Design of active databases: termination, confluence, determinism, modularisation.

Temporal Databases

Temporal data and applications. Time ontology. Conceptual modeling of temporal aspects. Manipulation of temporal data with standard SQL.

Graph Databases

Spatial Databases

Spatial data and applications. Space ontology. Conceptual modeling of spatial aspects. Manipulation of spatial data with standard SQL.

Reference Books

  • C. Zaniolo et al., Advanced Database Systems, Morgan Kaufmann, 1997
  • R.T. Snodgrass, Developing Time-Oriented Database Applications in SQL, Morgan Kaufmann, 2000 (version pdf)
  • Tom Johnston, Bitemporal Data: Theory and Practice, Morgan Kaufmann, 2014
  • R.T. Snodgrass, The TSQL2 Temporal Query Language, Kluwer Academic Publishers, 1995
  • S.W. Dietrich, S.D. Urban, Fundamentals of Object Databases: Object-Oriented and Object-Relational Design, Morgan & Claypool, 2011
  • Jim Melton and Alan R. Simon, SQL: 1999 - Understanding Relational Language Components, Morgan Kaufmann, 2001
  • Jim Melton, Advanced SQL: 1999 - Understanding Object-Relational and Other Advanced Features, Morgan Kaufmann, 2002
  • Ian Robinson, Jim Webber, Emil Eifrem, Graph Databases, 2nd Edition, O'Reilly Media, 2015
  • Philippe Rigaux, Michel Scholl, Agnès Voisard, Spatial Databases: With Application to GIS, Morgan Kaufmann, 2001

Additional documentation

  • Norman W. Paton, Oscar Díaz, Active Database Systems, ACM Computer Surveys, 31(1): 63-103, 1999. (version pdf)
  • Jennifer Widom, The Starbust Active Database Rule System, IEEE Transactions on Knowledge and Data Engineering, 8(4): 583-595 1996 (version pdf)
  • E. Zimányi, Temporal Aggregates and Temporal Universal Quantifiers in Standard SQL, SIGMOD Record, 35(2):16-21, 2006. (version pdf)
  • Krishna Kulkarni, Jan-Eike Michels, Temporal features in SQL:2011, SIGMOD Record, 41(3):34-43, 2012. (version pdf)
  • Michael H. Böhlen, Anton Dignös, Johann Gamper, Christian S. Jensen, Temporal Data Management: An Overview, Proc. of the 7th European Summer School on Business Intelligence and Big Data, eBISS 2017, Bruxelles, Belgium, LNBIP 324, Springer 2018. (version pdf) * Gregory Sannik, Fred Daniels, Enabling the Temporal Data Warehouse, Teradata White paper. (version pdf)
  • Richard T. Snodgrass, A Case Study of Temporal Data, Teradata White paper. (version pdf)
  • Teradata, Temporal Table Support. (version pdf)
  • Teradata, ANSI Temporal Table Support. (version pdf)
  • IBM, A Matter of Time: Temporal Data Management in DB2 for z/OS. (version pdf)

Course Slides



Students, in groups of four students, will realize a project in a topic relevant to advanced databases. Examples of topics are given in the next section of this document. Please notice that the template for these topics is “<Technology> with <Tool1> and <Tool2>”.

Each group will study a database technology (e.g., document stores, time series databases, etc.) and illustrate it with an application developed ​​in two database management systems to be chosen (e.g., SQL Server, PostgreSQL, MongoDB, etc.). The topic should be addressed in a technical way, to explain the foundations of the underlying technology. The application must use the chosen technology. Examples of technologies and tools can be found for example in the following web site.

It is important to understand that the objective of the project is NOT about developing an application with a GUI. The objective is to benchmark the proposed tool in relation to the database requirements of your application. Therefore, it is necessary to determine the set of queries and updates that your application requires and do a benchmark with, e.g., 1K, 10K, 100K, and 1M “objects” (rows, documents, nodes, etc. depending on the technology used) to determine if the tool shows a linear or exponential behavior. Please notice that you SHOULD NOT generate data for the benchmark since you can find in Internet (1) a huge number of available datasets (2) alternatively, there are many available data generators.

As usual when performing benchmarks, the queries and updates are executed n times (e.g., 6 times where the first execution is not considered because it is different from the others since the cache structures must be filled) and the average of the execution times is computed. A comparison with traditional relational technology (e.g., using PostgreSQL) must be provided to show that the chosen tool is THE technology of choice for your application, better than all other alternatives, and that it will perform correctly when the system is deployed at full scale. Please notice that there are MANY standard benchmarks for various database technologies so in that case you should prefer using a standard benchmark that reinventing the wheel and create your own benchmark.

The choice of topic and the application must be made ​​in agreement with the lecturer. The topic should not be included in the program of the Master in Computer Science and Engineering. The project will be presented to the lecturer and the fellow students at the end of the semester. This presentation will be supported by a slideshow. A written report containing the contents of the presentation is also required. The presentation and the report will (1) explain the foundations of the technology chosen, (2) explain how these foundations are implemented by the database management systems chosen and (3) illustrate all these concepts with the application implemented.

The duration of the presentation is 45 minutes. It will structured in three parts of SIMILAR length

  • An introduction to technology
  • An introduction to the two tools, each presented by a subgroup of two persons
  • A common assessment of the advantages and disadvantages of both tools tested in a common example application.

The evaluation of the project focuses on the following criteria:

  • Quality of the presentation,
  • Master of the topic presented, and
  • Quality of written report.

The project will count for 25% of the final grade.

The project must be submitted by Monday, December 12, 2022. Please send the report and the presentation in PDF format to the lecturer.

  • Cloud databases and Microsoft Azure, AWS, …
  • Column stores and Cassandra, Hbase, …
  • Data warehouses and Apache Hive
  • Distributed databases and SQL Server, Oracle, Citus, …
  • Document stores and Cloudant, Couchbase, CouchDB, MongoDB, RavenDB, RethinkDB, …
  • Embedded databases and BerkeleyDB
  • In-memory databases and Kdb+, MemSQL, Oracle TimesTen, Memcached, ….
  • Key-value stores and BerkeleyDB, DynamoDB, Redis, Voldermort, …
  • Multi-model databases and MarkLogic, CosmosDB
  • NewSQL databases and VoltDB, CockrachDB, …
  • Object-oriented databases and ObjectBox, Perst
  • Real-time databases and Firebase
  • Search engines and Solr, ElasticSearch, Sphinx …
  • Spatial raster databases and Rasdaman
  • Stream databases and Apache Kafka, Event Stores
  • Time series databases and Influx DB, Kdb+, …
  • XML databases and BaseX

Topics for the current academic year

  • Microsoft Azure and Google Cloud SQL: Marques Correia Tiago, Kellian Germain, Sébastien Arte, Nehili Adel
  • Document databases with ArangoDB and MarkLogic: Mir Wise Khan, Rishika Gupta, Ahmad, Chidiebere Ogbuchi
  • Document databases with MongoDB and CouchBase: Abd Abu Sbei, Hoschek Maren, Gupta Prashant, TBD
  • Document databases with CouchDB and RavenDB: Aissa Abdoul-Aziz, Helin Demirel, Imane Moussaoui, Salma Mekarnia
  • Embedded databases and BerkeleyDB and CouchBase Lite: Talhaoui Yassin, Arfani Abdessamad, Faek Ilias, Adegnon Kokou
  • Key-value databases with etcd and Hazelcast: Liliia Aliakberova, Arina Gepalova, Jose Antonio Lorencio Abril, Mariana Mayorga Llano
  • Key-value databases with OrientDB and Memcached: Mustapha Ayadi, Valentin De Baene, Soumaya Izmar, Yi Zhu
  • Oriented Object Databases with ObjectBox and Perst: Belgada Naoufal, El Hamri Ayoub, Akroune Sami, Sif Eddine Boughris
  • RDF databases with Virtuoso and Apache Jena: Nikola Ivanović, Bogdana Živković, Tianheng Zhou, You Xu
  • Search engines with ElasticSearch and OpenSearch: Muhammad Rizwan Khalid, Sayyor Yusupov, Ali Abusaleh, Ali Belyazid
  • Search engines databases with Solr and Manticore Search: Rachel Aouad Albshara, Loïc Cordeiro Fonseca, Quentin Magron, Dang Phi L. Pham
  • Stream Databases with PipelineDB and HStreamDB: Idil Dikbas, Ehsan Gifani, TBD, TBD
  • Time Series databases with InfluxDB and KDB: Luis Alfredo León, Jezuela Gega, Satria Wicaksono, Isabella Forero
  • Timeseries databases with TimescaleDB and QuestDB: Koumudi Ganepola, Adina Bondoc, Zyad Al-Azazi, Alaa Almutawa
  • Wide column stores with Cassandra and HBase: Anthony Zhou, Arnaud Cools, Damien Decleire, Thomas Dudziak

Examinations from Previous Years

teaching/infoh415.txt · Last modified: 2022/11/29 17:51 by ezimanyi