INFO-H-415: Advanced Databases


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 Thursdays from 2 pm to 4 pm at the room S.UA4.218
  • Exercises on Mondays from 4 pm to 6 pm at the room S.UB4.130



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.

Object Databases

Object-oriented model. Object Persistance. ODMG standard: Object Definition Language and Object Query Language.

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
  • R.G.G. Cattel et al., The Object Database Standard: ODMG 3.0, Morgan Kaufmann, 2000 (version pdf)
  • 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)
  • 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)
  • Temporal databases
    • TimeCenter, an international research centre for temporal databases.
    • TimeDB, a temporal relational database
  • Object databases
  • Post-relationnal databases

Course Slides



Students, in groups of two, will realize a project in a topic relevant to advanced databases. Examples of topics are given in the next section of this document.

Each group will study a database technology and illustrate it with an application developed ​​in a database management system to be chosen (e.g., Oracle, PostgreSQL, DB2, SQL Server, mySQL, etc..). The topic should be addressed in a technical way, to explain the underlying technologies. The application must use the specific technology manipulated.

The choice of topic and the application must be made ​​in agreement with the lecturer. The topic should not be included in the programme 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 written report will explain the possibilities offered by the database management system chosen and give a general description of the application implemented.

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 17, 2018.

Examples of topics from the previous academic year

You can take a look at the DB-Engines web site to get an idea of the currently available technologies and tools. Examples of previous topics are given next:

  • Analytical databases and Endeca
  • Cloud databases and Microsoft Azure
  • Column stores and Cassandra, Hbase, …
  • Deductive Databases and XSB
  • Distributed databases and SQL Server, DynamoDB, …
  • Document stores and Cloudant, Couchbase, CouchDB, MongoDB, RavenDB, RethinkDB, …
  • Embedded databases and BerkeleyDB
  • Graph Databases and Neo4J, OrientDB, …
  • In-memory databases and Kdb+, MemSQL, Oracle TimesTen, ….
  • Key-value stores and Redis, Voldermort, …
  • Multimedia databases and Oracle
  • Multi-model databases and MarkLogic
  • NewSQL databases and VoltDB
  • Object-oriented databases and db4o
  • Real-time databases and Firebase
  • XML databases and BaseX

Topics for the current academic year

  • Cloud databases and Microsoft Azure: Sara Diaz, Buse Ozer
  • Deductive databases and XSB: Gonçalo Moreira, Kaoutar Chennaf
  • Distributed messaging with Apache Kafka: René Gómez Londoño, Ankush Sharma
  • Distributed databases and DynamoDB: Elena Ouro, Carlos Badillo
  • Distributed databases and Apache Hive: Ricardo Rojas, Danilo Acosta
  • Document stores and MongoDB: Sivaporn Homvanish, Tzu-Man Wu
  • Document stores and CouchBase: Carlos Martinez Lorenzo, Pablo Molina Mata
  • Document stores and CouchDB: Aparna Khire, Mingrui Dong
  • Embedded databases and Berkeley DB: Ainhoa Zapirain, Nazrin Najafzade
  • In-memory databases and MemSQL: Haydar Ali Ismail, Dwi Prasetyo Adi Nugroho
  • Key-value stores and Redis: Amritansh Sharma, Haftamu Hailu
  • Key-value stores and Memcached: Nathan Hullebroeck, Julien Delbeke
  • Multi-Model databases and MarkLogic: Nathan Hullebroeck, Julien Delbeke
  • NoSQL databases and Cassandra: Pratham Solanki, Braulio Blanco
  • Object-oriented databases and db4o: Pinar Turkyilmaz, Annemarie Burger
  • Real-time databases and Firebase: Pablo Lopez, Maria Gabriela Martinez
  • Search engines and ElasticSearch: Ioannis Prapas, Sokratis Papadopulos
  • Search engines and Sphinx: Kevin SEFU, Antonio RAFAELE, Nestor RAMOS PEREZ
  • Spatial data and Rasdaman: Fernando Mendes Stefanini, Evgeny Pozdeev
  • Time series databases and Influx DB: Shabana Salmaan, Danish Amjad
  • Time series databases with Kdb+: Eugen Robert Patrascu, Kunal Arora
  • Wide-column databases and Apache HBase: Edoardo Conte, Carlos E. Muniz Cuza
  • XML databases and BaseX: Marine Devers, Richard Bauwens

Examinations from Previous Years

teaching/infoh415.txt · Last modified: 2018/11/12 13:07 by ezimanyi