Mining of Massive Datasets
by Anand Rajaraman, Jeffrey D. Ullman
Publisher: Stanford University 2010
Number of pages: 340
At the highest level of description, this book is about data mining. However, it focuses on data mining of very large amounts of data, that is, data so large it does not fit in main memory. Because of the emphasis on size, many of our examples are about the Web or data derived from the Web.
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by Tom Jewett
This text is a teaching resource for an introductory database class at California State University Long Beach, Department of Computer Engineering and Computer Science. It is also designed to be used as an individual self-study tutorial.
by P. A. Bernstein, V. Hadzilacos, N. Goodman - Addison Wesley
This book is about techniques for concurrency control and recovery. It covers techniques for centralized and distributed computer systems, and for single copy, multiversion, and replicated databases. Example applications are included.
by Adrienne Watt - BCcampus
The purpose of this text is to provide an open source textbook that covers most introductory database courses. This edition covers database systems and database design concepts. New to this edition are SQL info, additional examples, and exercises.
by E. F. Codd - Addison-Wesley
Written by the originator of the relational model, the book covers the practical aspects of the design of relational databases. The author defines twelve rules that database management systems need to follow in order to be described as relational.