Scalable Data Management Systems (SDMS)

This course introduces the fundamental concepts and computational paradigms of scalable data management systems. The focus of this course is on the systems-oriented aspects and internals of such systems for storing, updating, querying, and analyzing large datasets.

Teaching Mode:
We will employ a mainly in-person teaching setup for this course in the winter term 2023 while some lectures might be given online. We will announce ahead of time if a lecture is given online. Please follow the links to Moodle for more information.

Quick Links

Organization

Last offered Winter Semester (23/24)
Lecturer Prof. Dr. Carsten Binnig, Prof. Dr. Zsolt István
Assistants Jigao Luo, Long Gu, Nils Boeschen
Exam Graded programming projects & 60min written exam
See TUCaN link above for additional information (e.g., rooms & appointments)
  • Database Architectures
  • Parallel and Distributed Databases
  • Data Warehousing
  • MapReduce and Hadoop
  • Spark and its Ecosystem
  • Optional: NoSQL Databases, Stream Processing, Graph Databases, Scalable Machine Learning

Recommended literature include:

  • Garcia-Molina et. al.: Data Systems Implementation
  • Silberschatz et. al.: Database Systems Concepts
  • Ramakrishnan et. al.: Database Management Systems
  • T. Özsu et. al.: Principles of Distributed Database Systems