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.
Due to the current COVID-19-situation, all teaching activities will be completely online: courses will be either given as live stream (with recordings) or as video lectures (offline recordings). The detailed setup for each course regarding the organization will be announced on the Moodle website of each course. Please follow the links to Moodle.
Quick Links
Course materials & Forum (Moodle) – Registration & Detailed Info (TUCaN)
Organization
| Last offered | Winter Semester (20/21) |
| Lecturer | Prof. Dr. Carsten Binnig |
| Assistants | Muhammad El-Hindi, Nils Boeschen |
| Exam | Graded programming projects & 60min written exam |
| See TuCAN link above for additional information (e.g., rooms & appointments) | |
Content
- 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
Literature
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