CMPT 843: Traditional vs. Modern Database Systems (SFU, Spring 2018)


The Big Data movement is attracting an increasing number of new researchers to work on data processing related research. On the other hand, the database community has been thinking about how to address data-processing challenges for over 40 years. Numerous elegant ideas were proposed in the past and many of them are being widely applied in industry. Therefore, there is a high need to educate new researchers to learn classical database knowledge and make sure they can stand on the shoulders of giants rather than reinvent the wheel.


Because of the purpose above, the course will be divided into two parts.

  1. The first part will guide students to read classical database papers that were published before 2000 on the topics including Data Model, Relational Database Systems, Transaction Management, Query Optimization, Data Warehouse, and Approximate Query Processing.
  2. The second part will be mostly about the papers published in the recent ten years on the topics including MapReduce, Spark, Column Store, NoSQL, NewSQL, and ML over SQL.


Through this traditional vs. modern view of data processing, the students should gain a much deeper understanding of the Big Data movement and form their own opinion on what's novel about Big Data systems.

Furthermore, since this is a graduate seminar, another important objective is to train students to master basic skills for being a researcher. The course will create a number of opportunities for students to learn how to read a paper, how to write a paper review, how to give a good research talk, and how to ask questions during a talk?




Blog Post

Final Project