Time Mon, Wed 2:50pm-4:30pm
Location RB 109 (Robinson Hall)
(except for 11/2 which will be via Zoom)

Course Team & Getting-in-Touch

Please communicate with us regularly. If you don’t understand something, please ask questions! We love questions. One of the benefits of attending a university and interactive classes as opposed to reading a book is that you get to interact with faculty, TAs, and your peers. We are continuously striving to become better and several questions of students who have attended this or similar classes in the past have helped me (Wolfgang) think about some of the illustrative examples you see in class. If at all possible, please reach out to us with your questions via Piazza (linked to from within Canvas), so whoever of us is at hand can answer your question first, plus your peers can see the discussion and join the conversation. You can also leave anonymous feedback via this anonymous Google form, which only I can see. If you want to send me a private message, please use email, not Piazza nor Canvas.

Wolfgang Gatterbauer (Instructor)

Office Hours directly after class (preferred), or
Wed 8:30am-9am @WVH450 (9/14-12/7, except 11/2 & 11/23), or
via Microsoft Teams scheduled by email (in your email to me, please state topic and propose 3 different time slots I can choose from)

Neha Makhija (Head Teaching Assistant)

Office Hours Tue 3pm-5pm @WVF 116 (9/13-12/6), or
Thu 10am-noon @WVH 3rd floor open work area (go right when exciting elevators, near the windows and whiteboards)

Grishma Rajendra Alshi (Teaching Assistant)

Office Hours Thu 1pm-3pm @WVH 3rd floor open work area (go right when exciting elevators, near the windows and whiteboards)


This course builds upon the structure and content of several existing database classes at University of Washington, Cornell, Stanford and Technion with various modifications to make the material suitable earlier in the curriculum (at most other colleges, databases are taught with an eye towards database internals and thus come at the end of the studies after strong algorithmic foundations are established). Some content courtesy to Ramakrishnan-Gehrke (authors of the "cow" database book), Dan Suciu (my former Postdoc advisor), Magda Balazinska, Gerome Miklau, Yanlei Diao, Alexandra Meliou, Cris Re, Peter Bailis, Andy Pavlo, and Benny Kimelfeld. Also full credit to Nate Derbinsky for the slick course web page design.