Whether you're a database designer, programmer, analyst, or manager, you've probably encountered some of the challenges-and experienced some of the frustrations-associated with time-varying data. Where do you turn to fix the problem and see that it doesn't happen again? In Developing Time-Oriented Database Applications in SQL , a leading SQL researcher teaches you effective techniques for designing and building database applications that must integrate past and current data. Written to meet a pervasive, enduring need, this book will be indispensible if you happen to be part of the flurry of activity leading up to Y2K.
The enclosed CD-ROM contains all of the code fragments-implemented for Oracle8 Server, IBM DB2 Universal Database, Microsoft SQL Server, and other systems-and evaluation copies of the programs discussed in the book.
* Offers incisive advice on recording temporal data using SQL data types, defining appropriate integrity constraints, updating temporal tables, and querying temporal tables with interactive and embedded SQL. * Provides case studies detailing real-world problems and solutions in areas such as event data, state-based data, partitioned data, and audit logs. * Contains over 400 code fragments with detailed explanations.
Seems that the author really knows the subject. The book contains lots of examples and can be used as a reference to implementing a bi-temporal database.
Not sure if I wanna recommend this, since it's not an easy read and I somehow think that there might be better books out there about temporal databases. Definitely not a useless book, though.
This book very nice explains the issue of dealing with time in relational databases. It goes in to detail explaining the basics of date and time (duration, period, interval, instance, etc.) and how it can be stored.
The book was written in 1998, so some of the SQL in it is no longer valid. But I'd still recommend it for a junior developer to read it.
Great book. Everyone who is thinking about periods of entities and different conditions - the best read. Normalization for time-oriented records. Will save you alot of time.