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teaching:infoh415 [2019/11/28 18:03] ezimanyi [Topics for the current academic year] |
teaching:infoh415 [2020/12/10 15:56] (current) ezimanyi [Project] |
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| * [[http://www.google.com/calendar/embed?src=dug2eihu8tqtnkjhmtuupj0je0%40group.calendar.google.com&ctz=Europe/Brussels|Online schedule]] | * [[http://www.google.com/calendar/embed?src=dug2eihu8tqtnkjhmtuupj0je0%40group.calendar.google.com&ctz=Europe/Brussels|Online schedule]] | ||
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| ===== Objectives ===== | ===== Objectives ===== | ||
| 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. | 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. | ||
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| ===== Content ===== | ===== Content ===== | ||
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| - | 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. | + | 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. Please notice that the template for these topics is "<Technology> and <Tool>". |
| - | 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..). | + | Each group will study a database technology and illustrate it with an application developed in a database management system 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. |
| - | 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. | + | It is important to understand that the objective of the project is NOT about developing an application with 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. 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 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. |
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| + | 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 system chosen and (3) illustrate all these concepts with the application implemented. | ||
| The evaluation of the project focuses on the following criteria: | The evaluation of the project focuses on the following criteria: | ||
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| The project will count for 25% of the final grade. | The project will count for 25% of the final grade. | ||
| - | The project must be submitted by **Monday, December 16, 2019**. | + | The project must be submitted by **Monday, December 14, 2020**. |
| ===== Examples of topics from the previous academic year ===== | ===== Examples of topics from the previous academic year ===== | ||
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| * Real-time databases and Firebase | * Real-time databases and Firebase | ||
| * Search engines and Solr, ElasticSearch, Sphinx ... | * Search engines and Solr, ElasticSearch, Sphinx ... | ||
| - | * Spatial databases and Rasdaman | + | * Spatial raster databases and Rasdaman |
| * Stream databases and Apache Kafka | * Stream databases and Apache Kafka | ||
| * Time series databases and Influx DB, Kdb+, ... | * Time series databases and Influx DB, Kdb+, ... | ||
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| ===== Topics for the current academic year ===== | ===== Topics for the current academic year ===== | ||
| - | * Analytics data warehouse and Google BigQuery: Hridaya Sagar Subedi, Alp Albay | + | * Analytical databases and Endeca: Ndele-A-Mulenghe Mashini |
| - | * Cloud databases and Microsoft Azure: Rodaina Mohamed, Karim Maatouk | + | * Cloud databases and Microsoft Azure: Michel Nguyen-Khan and Soufian El Bakkali Tamara |
| - | * Column stores and Cassandra: Andrea Armani, Anant Gupta | + | * Column stores and Cassandra: Wassil Choujaa and Ismaila Abdoulahi Adamou |
| - | * Data warehouses and Apache Hive: Emir Nurmatbekov, Mahmudul Hasan | + | * Distributed databases and SQL Server: Yasmina El Oudghiri |
| - | * Document stores and MongoDB: Ledia Isaj, Fabrício Ferreira | + | * Document stores and MongoDB: Beata Janiak and Astrid Asoumoy |
| - | * Document stores and Couchbase: Samia Azzouzi, Brahim Amssafi | + | * Key-value databases and BerkeleyDB: Mohamed Amchemer and Frank Jordan Kuete Kamta |
| - | * Document stores and CouchDB: Abdelilah El Majjaoui | + | * Key-value databases and DynamoDB: Abdeslam Bakkali Taheri and <TBD> |
| - | * Embedded Databases and BerkeleyDB: Ali Arous, Maria Letizia Losso | + | * Key-value databases and Redis: Yahya Bakkali and Maxime Hauwaert |
| - | * In-memory databases and Oracle TimesTen: Nathan Wolper, Kamdem Tagne Thomas Borel | + | * Multimedia databases and Oracle: Fan Chen and Noëmie Muller |
| - | * Key-value stores and Redis: Ira nazarchuk, Julio Candela | + | * NewSQL databases and VoltDB: Sid Ahmed Bouzouidja and Louis-Maxime Piton |
| - | * Multimedia databases and Oracle: Muthi Dorel Adrian, Fan Chen | + | * Object-oriented databases and Perst: Nicolas Boucher and Romain Perret |
| - | * Multimodel databases and MarkLogic: Gian Marco Paldino, Piotr Rochala | + | * Object-oriented databases and ObjectBox: Ajouaou Soufiane and El Achouchi Iliass |
| - | * Multimodel databases and Microsoft Azure Cosmos DB: Dimitrios Tsesmelis, Ricardo Holthausen Bermejo | + | * Real-time databases and Firebase: Ali Dhanani and Cleis Kounalis |
| - | * NewSQL databases and VoltDB: Tamara Bojanic, Iva Mihajlovska | + | * Search engines and Solr, ElasticSearch: Tatiana Millan Poveda and Erick Escobar Gallardo |
| - | * Object-oriented databases and Versant: Yi Chiau Li, Yu Hsuan Chen | + | * Stream databases and Apache Kafka, Event Stores: Alexandre Libert and Antoine De Selys |
| - | * Real-time databases and Firebase: Jesus Huete, Valdemar Hernández | + | * Time series databases and InfluxDB: Nada Elghazouani and Jean-Charles Nsangolo |
| - | * Search Engines and Elastic Search: Haroon Rashid, Djordjije Krivokapic | + | * XML databases and BaseX: Sara Bouglam |
| - | * Search Engines and ELK stack with Kafka: Haftamu Hailu Tefera, Ishaan Rachit Dwivedi | + | |
| - | * Streaming Databases with Apache Kafka: Nithish Sankaranarayanan, Gayane Vardanyan | + | |
| - | * Stream Processing and Apache Storm: Ariston Harianto Lim, Hung Nguyen | + | |
| - | * Stream processing and SQL stream: Sheida Shafiee Sarvestani, Nicolas Feron | + | |
| - | * Time series databases and InfluxDB: Yalei Li, Haonan Jin | + | |
| - | * Time series databases and TimescaleDB: Uchechukwu Fortune Njoku, Akash Malhotra | + | |
| - | * XML databases and BaseX: Ayman Mountasser, Mohammed Amine Belfarsi | + | |
| - | /* * {{:teaching:infoh415:student_projects:2019:azure.pdf|Cloud databases and Microsoft Azure}}: Sara Diaz, Buse Ozer */ | ||
| ===== Examinations from Previous Years ===== | ===== Examinations from Previous Years ===== | ||