The main objectives of this graduate-level course are to provide an in-depth understanding of advanced concepts and research directions in the field of databases. The course is organized in three parts: (i) Fundamentals of Database Systems Implementation; (ii) Distributed, Web and Cloud Databases; (iii) Spatio-temporal Data Management, Sensor Data Management, other selected and advanced topics from the recent scientific literature.
Outline: (i) Fundamentals of modern Database Management Systems (DBMSs): storage, indexing, query optimization, transaction processing, concurrency and recovery. (ii) Fundamentals of Distributed DBMSs, Web Databases and Cloud Databases (NoSQL / NewSQL): Semi-structured data management (XML/JSON, XPath and XQuery), Document data-stores (i.e., CouchDB, MongoDB, RavenDB), Key-Value data-stores (e.g., BerkeleyDB, MemCached), Introduction to Cloud Computing (GFS, NFS, Hadoop HDFS, Replication/Consistency Principles), "Big-data" analytics (MapReduce, Apache's Hadoop, PIG), Column-stores (e.g., Google's BigTable, Apache's HBase, Apache's Cassandra), Graph databases (e.g., Twitters FlockDB) and Overview of NewSQL (Google's Spanner and Google's F1). (iii) Spatio-temporal data management (trajectories, privacy, analytics) and index structures (e.g., R-Trees, Grid Files) as well as other selected and advanced topics, including: Embeeded Databases (sqlite), Sensor / Smartphone / Crowd data management, Energy-aware data management, Flash storage, Stream Data Management, etc. The last part of the course will feature both invited talks from external invited speakers and the presentations of students.
Course Website: http://www.cs.ucy.ac.cy/~dzeina/courses/epl646/