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teaching:infoh415 [2019/11/28 18:03]
ezimanyi [Topics for the current academic year]
teaching:infoh415 [2025/02/04 13:32] (current)
ezimanyi [Examinations from Previous Years]
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 ====== INFO-H-415: Advanced Databases ====== ====== INFO-H-415: Advanced Databases ======
 +
  
  
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 ===== Teaching Assistant ===== ===== Teaching Assistant =====
  
-  * [[Gilles.Dejaegere@ulb.ac.be|Gilles Dejaegere]]+  * [[boris.coquelet@ulb.be|Boris Coquelet]]
  
  
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 The course is given during the first semester ​ The course is given during the first semester ​
-  * Lectures on Mondays from 4 pm to 6 pm at the room S.AY2.108 **except 14/10/2019 which is a practical session in S.UB4.130** +  * Lectures on Mondays from 4 pm to 6 pm 
-  * Exercises on Thursdays from 2 pm to 4 pm at the room S.UB4.130 <​del>​**except 24/10/2019 which is a lecture in S.UD2.119** +  * Exercises on Thursdays from 2 pm to 4 pm
-</​del>​+
  
 /*  /* 
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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]]
 */ */
 +
 +
 +===== Grading =====
 +  * Group project (25%)
 +  * Written exam (75%)
 +    * the exam is open book; notes and books can be used. Laptops and other electronic devices are **not** allowed. Please prepare your paper material in advance, not the day before the examination to avoid any printing problems
 +
 +
 ===== 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.
 +
 +
 +
 ===== Content ===== ===== Content =====
  
-==== Active ​Databases ====+==== Spatial ​Databases ====
  
-Taxonomy ​of conceptsApplications ​of active databases: integrity maintenance,​ derived ​data, replicationDesign of active databases: termination,​ confluence, determinism,​ modularisation.+Spatial data and applications. Space ontology. Conceptual modeling ​of spatial aspectsManipulation ​of spatial ​data with standard SQL. 
 + 
 +==== Mobility Databases ==== 
 + 
 +...
  
 ==== Temporal Databases ==== ==== Temporal Databases ====
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 Temporal data and applications. Time ontology. Conceptual modeling of temporal aspects. Manipulation of temporal data with standard SQL. Temporal data and applications. Time ontology. Conceptual modeling of temporal aspects. Manipulation of temporal data with standard SQL.
  
-==== Graph Databases ====+==== Active ​Databases ====
  
-...+Taxonomy of conceptsApplications of active databases: integrity maintenance,​ derived data, replicationDesign of active databases: termination,​ confluence, determinism,​ modularisation.
  
-==== Spatial Databases ==== 
- 
-Spatial data and applications. Space ontology. Conceptual modeling of spatial aspects. Manipulation of spatial data with standard SQL. 
  
  
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   * Tom Johnston, Bitemporal Data: Theory and Practice, Morgan Kaufmann, 2014   * Tom Johnston, Bitemporal Data: Theory and Practice, Morgan Kaufmann, 2014
   * R.T. Snodgrass, The TSQL2 Temporal Query Language, Kluwer Academic Publishers, 1995   * 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 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   * 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   * Philippe Rigaux, Michel Scholl, Agnès Voisard, Spatial Databases: With Application to GIS, Morgan Kaufmann, 2001
  
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   * IBM, A Matter of Time: Temporal Data Management in DB2 for z/OS. ({{teaching:​infoh415:​a_matter_of_time.pdf|version pdf}})   * IBM, A Matter of Time: Temporal Data Management in DB2 for z/OS. ({{teaching:​infoh415:​a_matter_of_time.pdf|version pdf}})
 ===== Links ===== ===== Links =====
-  * Temporal ​databases  +  * Spatial ​databases 
-    * [[http://timecenter.cs.aau.dk/|TimeCenter]], an international research centre for temporal databases. +    * [[https://postgis.net/​workshops/​postgis-intro/|Introduction to PostGIS]] 
-    * [[http://www.timeconsult.com/Software/Software.html|TimeDB]], a temporal relational database+    * [[https://learn.crunchydata.com/postgis|Crunchy Data Interactive PostGIS Learning Portal]] 
 +  * Mobility databases 
 +    * [[https://mobilitydb.com/|MobilityDB]]  
   * Object databases   * Object databases
     * [[http://​www.odbms.org/​|ODBMS.ORG]],​ portal of ressources about object databases.     * [[http://​www.odbms.org/​|ODBMS.ORG]],​ portal of ressources about object databases.
-    * [[http://​www.db4o.com/​|db4o]],​ an open source object database. 
     * [[http://​www.objectstore.com/​datasheet/​index.ssp|ObjectStore]],​ an object database     * [[http://​www.objectstore.com/​datasheet/​index.ssp|ObjectStore]],​ an object database
     * [[http://​www.objectivity.com|Objectivity]],​ an object database     * [[http://​www.objectivity.com|Objectivity]],​ an object database
-    * [[http://​www.versant.com/​|Versant]],​ an object database 
-    * [[http://​www.jade.co.nz/​jade/​|Jade]],​ an object database 
-    * [[http://​sourceforge.net/​projects/​ozone/​|Ozone]],​ an object database 
   * Post-relationnal databases   * Post-relationnal databases
-    * [[http://​www.fresher.com/​|Matisse]] 
     * [[http://​www.intersystems.com/​cache/​index.html|Caché]]     * [[http://​www.intersystems.com/​cache/​index.html|Caché]]
-  * Spatial databases 
-    * [[https://​postgis.net/​workshops/​postgis-intro/​|Introduction to PostGIS]]  ​ 
  
 ===== Course Slides ===== ===== Course Slides =====
  
-  * {{teaching:​infoh415:​activenotes.pdf|Active databases}} 
-  * {{teaching:​infoh415:​temporalnotes.pdf|Temporal databases}} 
-/*   * {{teaching:​infoh415:​objectnotes.pdf|Object databases}} ​  */ 
-  * {{:​teaching:​infoh415:​graph_databases_notes.zip|Graph Notes}} 
   * {{teaching:​infoh415:​spatialnotes.pdf|Spatial databases}}   * {{teaching:​infoh415:​spatialnotes.pdf|Spatial databases}}
 +  * Mobility databases
 +  * {{teaching:​infoh415:​temporalnotes.pdf|Temporal databases}}
 +  * {{teaching:​infoh415:​activenotes.pdf|Active databases}}
 +/*  * {{:​teaching:​infoh415:​graphdb-ulb-2021.zip|Graph Notes (2021 version)}} */
 +/*   * {{teaching:​infoh415:​objectnotes.pdf|Object databases}} ​  
 +  * {{:​teaching:​infoh415:​graph_databases_notes.zip|Graph Notes}}*/
  
  
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   * [[teaching:​infoh415:​TP|Exercices Web page]]   * [[teaching:​infoh415:​TP|Exercices Web page]]
 +
 ===== Project ===== ===== Project =====
  
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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 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 and illustrate it with an application developed ​​in ​database management ​system ​to be chosen (e.g., Oracle, PostgreSQL, DB2, SQL Server, ​mySQL, etc..). +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 ​ [[https://​db-engines.com/​en/​ranking|web site]].
-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 general description ​of the application ​implemented.+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 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: 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 **immediately after** the project presentationwhich will take place on the week on Monday ​December 16, 2024Please send the report and the presentation in PDF format to the lecturer. ​
- +
-===== Examples of topics from the previous academic year =====+
  
-You can take a look at the [[https://​db-engines.com/​en/​|DB-Engines]] web site to get an idea of the currently available technologies and tools. Examples of previous topics are given next: +  ​* Cloud databases and Microsoft Azure, AWS, ...
- +
-  * Analytical databases and Endeca +
-  ​* Cloud databases and Microsoft Azure+
   * Column stores and Cassandra, Hbase, ...   * Column stores and Cassandra, Hbase, ...
   * Data warehouses and Apache Hive   * Data warehouses and Apache Hive
-  ​* Deductive Databases and XSB +  * Distributed databases and SQL Server, ​Oracle, Citus, ...
-  ​* Distributed databases and SQL Server, ​DynamoDB, ...+
   * Document stores and Cloudant, Couchbase, CouchDB, MongoDB, RavenDB, RethinkDB, ...   * Document stores and Cloudant, Couchbase, CouchDB, MongoDB, RavenDB, RethinkDB, ...
   * Embedded databases and BerkeleyDB   * Embedded databases and BerkeleyDB
   * In-memory databases and Kdb+, MemSQL, Oracle TimesTen, Memcached, ....   * In-memory databases and Kdb+, MemSQL, Oracle TimesTen, Memcached, ....
-  * Key-value stores and Redis, Voldermort, ... +  * Key-value stores and BerkeleyDB, DynamoDB, ​Redis, Voldermort, ... 
-  * Multimedia databases and Oracle +  * Multi-model databases and MarkLogic, CosmosDB 
-  * Multi-model databases and MarkLogic +  * NewSQL databases and VoltDB, CockrachDB, ... 
-  * NewSQL databases and VoltDB +  * Object-oriented databases and ObjectBox, Perst
-  * Object-oriented databases and db4o+
   * 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, Event Stores
   * Time series databases and Influx DB, Kdb+, ...   * Time series databases and Influx DB, Kdb+, ...
   * XML databases and BaseX   * XML databases and BaseX
- 
  
 ===== Topics for the current academic year ===== ===== Topics for the current academic year =====
  
-  * Analytics data warehouse ​and Google BigQueryHridaya Sagar SubediAlp Albay +  * Document stores with MongoDB ​and PostgreSQLOluwanifemi Favour OlajuyigbeHadiqa Alamdar BukhariMathilde Lourenço, Hanling Hu 
-  * Cloud databases and Microsoft Azure: Rodaina MohamedKarim Maatouk +  * Document ​stores ​with Couchbase ​and CouchDBMarwah SulaimanSara Saad, Otto WantlandSebastian Neri  
-  * Column ​stores and CassandraAndrea ArmaniAnant Gupta +  * Document stores ​with Firebase Realtime Database ​and Google Cloud FirestoreGloria Akli-Kodjo-MensahJoel Anil Jose, Amélie Liesenborghs and Salma Namouri 
-  * Data warehouses and Apache Hive: Emir NurmatbekovMahmudul Hasan +  * Graph databases with Neo4j and Apache AGELucía FernándezStephanie Gomes, Filipe Russo, Elnara Yerbolatova 
-  * Document stores and MongoDBLedia IsajFabrício Ferreira +  * Graph databases with Aerospike ​and VirtuosoTim AmeryckxGilles Mevel, Antonios Sisiaridis, ​ Sacha Delsaux 
-  * Document stores ​and CouchbaseSamia AzzouziBrahim Amssafi +  * In-memory databases ​with Redis and MemcachedHilal RachikAya Iftissen, Antonio Baldari, Léoplod Guyot 
-  * Document stores ​and CouchDBAbdelilah El Majjaoui +  * Key-value stores ​with Redis and Amazon DynamoDBKerim EsievGeorge VasileRayane BaziMohammed Sewif 
-  * Embedded Databases and BerkeleyDB: Ali ArousMaria Letizia Losso +  * Key value stores with Memcached ​and AerospikeAnwar BoulahyaAntoine Frizot ​and Diogo Miguel Gonçalves Soares 
-  * In-memory databases and Oracle TimesTenNathan WolperKamdem Tagne Thomas Borel +  * Search engines with Sphinx ​and ElasticSearchAlfio Cardillo, Charlotte GarcíaJule Grigat, Josu Bernal 
-  * Key-value stores ​and Redis: Ira nazarchuk, Julio Candela +  * Search ​engines with Microsoft Azure SQL Database ​and Amazon Cloud Search: ​Dylane ZouatomNicola Mambelli, Jorge Del Rio Sanchez and Souha Belhaj Rhouma 
-  * Multimedia databases ​and OracleMuthi Dorel AdrianFan Chen +  * Search ​engines ​with Solr and PostgreSQLViet Phuong HoangNhu Ngoc Hoang, Ngoc Hoa Pham, Maureen Barral 
-  * Multimodel databases and MarkLogic: Gian Marco PaldinoPiotr Rochala +  * Stream databases ​with Apache Kafka and Amazon KinesisMoïra VanderslagmolenArthur InastalléJean-Nicolas ​Grégoire and Ze-Xuan Xu 
-  * Multimodel databases and Microsoft Azure Cosmos DB: Dimitrios TsesmelisRicardo Holthausen Bermejo +  * Time series databases ​with TimeScaleDB ​and InfluxDB: ​Kristóf Balázs, Stefanos Kypritidis, Olha BaliasinaNishant Sushmakar 
-  * NewSQL databases ​and VoltDBTamara BojanicIva Mihajlovska +  * Time series databases ​with Prometheus ​and GraphiteDerar AlnakebHugo Colicchia, Mohamad Sy, Aristide Coquereau ​ 
-  * Object-oriented databases ​and Versant: Yi Chiau Li, Yu Hsuan Chen +  * Vector ​databases ​with PGVector ​and ChromadbNima Kamali LassemAdrian Patricio, Kaiwen Yuan, Lianjie Li
-  * Real-time databases ​and FirebaseJesus HueteValdemar Hernández +
-  * Search ​Engines ​and Elastic ​Search: ​Haroon RashidDjordjije Krivokapic +
-  * Search ​Engines and ELK stack with KafkaHaftamu Hailu TeferaIshaan Rachit Dwivedi +
-  * Streaming Databases ​with Apache Kafka: Nithish Sankaranarayanan,​ Gayane Vardanyan +
-  * Stream Processing ​and Apache StormAriston Harianto LimHung Nguyen +
-  * Stream processing and SQL stream: Sheida Shafiee Sarvestani, Nicolas ​Feron +
-  * Time series databases and InfluxDB: ​Yalei LiHaonan Jin +
-  * Time series databases and TimescaleDBUchechukwu Fortune NjokuAkash Malhotra +
-  * XML databases and BaseXAyman MountasserMohammed Amine Belfarsi+
  
-/*  * {{:teaching:infoh415:student_projects:2019:azure.pdf|Cloud ​databases and Microsoft Azure}}Sara DiazBuse Ozer */ +/* 
-===== Examinations from Previous Years =====+  ​* ​Cloud databases with Microsoft Azure and AWSMaria Camila Salazar, Valerio Rocca, Ludovica Caiola, Simon Coessens 
 +  * Column stores with Cassandra and HBaseNoah Laravine, Clément Alloin, François Diximier 
 +  * Data warehousing with Google BigQuery and SnowflakeYutao Chen, Qianyun Zhuang, Min Zhang, Ziyong Zhang 
 +  * Distributed databases with YugaByteDB and CockroachDBSony Shrestha, Aayush Paudel, MD Kamrul Islam, Shofiyyah Nadhiroh 
 +  * Distributed databases with Apache Cassandra and CitusCatalina Correa, Vassili Papadakis, Paeg Hing Leong, Mohamed Bouchkhachakh 
 +  * Document stores with CouchDB and MongoDB: Aryan Gupta, Dilbar Isakova, Hareem Raza, Muhammad Qasim Khan 
 +  * Document stores with RavenDB and RethinkDB: Leila Bourouf, Nargis Sghiouar, Joel Niarisi 
 +  * Embedded ​databases ​with Berkeley DB et SQLite: Alexandre Dubois, Adel Nehili, Edgardo Cuellar Sanchez, Shri-Krishna Mungur 
 +  * Graph databases with Neo4J and OrientDBGabriela KaczmarekBerat Furkan Koçak, Jakub Kwiatkowski,​ Arijit Samal 
 +  ​Graph databases with TigerGraph and Memgraph: Melissa Tsombeng, Thomas Borremans 
 +  * Key-value stores with Redis and Amazon DynamoDB: Dionisius Mayr, Herma Elezi, Rana İşlek, Thomas Suau 
 +  * NewSQL Databases with CockroachDB and NuoDB: Onur Bacaksız, Emmanuel Leguede, Narmina Mahmudova, Mohamed Louai Bouzaher 
 +  * Object databases with Object Box and Zope: Nadine Guettat, Suman Khan, Naoufal Belgada, Latoundji Salim 
 +  * Real time database avec Firebase et Redis: Mathieu Van den Bremt, Nabil Abdellaoui, Elliot Silberwasser,​ Arkadiusz Snarski 
 +  * Search engines with Elasticsearch and Solr: Benjamin Gold, Quentin Demonceau, Nils Van Es Ostos, David García Morillo 
 +  * Stream databases with Kafka and EventStoreDB:​ Noubissi Kamgang Allan, Talhaoui Youssef, Gauthier Roger France, Stevens Quentin 
 +  * Stream databases with Apache Flink and Apache Storm: Jintao Ma, Linhan Wang, Iyoha Peace Osamuyi, Hieu Nguyen 
 +  * Time series databases with InfluxDB and Kdb: Gian Tejada Gargate, Gabriel Lozano Pinzón, José Carlos Lozano Dibildox, Enxhi Nushi 
 +*/
  
 +/*
 +  * 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 =====
 +  * Academic year 2024-2025
 +    * {{:​teaching:​infoh415_exam_jan25.pdf|First session}}
 +  * Academic year 2023-2024
 +    * {{:​teaching:​infoh415:​infoh415-2024-january.pdf|First session}}
   * Academic year 2016-2017   * Academic year 2016-2017
     * {{:​teaching:​infoh415:​infoh415-2017-january.pdf|First session}}     * {{:​teaching:​infoh415:​infoh415-2017-january.pdf|First session}}
 
teaching/infoh415.1574960625.txt.gz · Last modified: 2019/11/28 18:03 by ezimanyi