Time and date dimension in data warehouse
I'm building a data warehouse. Each fact has it's timestamp. I need to create reports by day, month, quarter but by hours too. Looking at the examples I see that dates tend to be saved in dimension tables. 
(source: etl-tools.info)
But I think, that it makes no sense for time. The dimension table would grow and grow. On the other hand JOIN with date dimension table is more efficient than using date/time functions in SQL.
What are your opinions/solutions ?
(I'm using Infobright)
Answer
Kimball recommends having separate time- and date dimensions:
design-tip-51-latest-thinking-on-time-dimension-tables
In previous Toolkit books, we have recommended building such a dimension with the minutes or seconds component of time as an offset from midnight of each day, but we have come to realize that the resulting end user applications became too difficult, especially when trying to compute time spans. Also, unlike the calendar day dimension, there are very few descriptive attributes for the specific minute or second within a day. If the enterprise has well defined attributes for time slices within a day, such as shift names, or advertising time slots, an additional time-of-day dimension can be added to the design where this dimension is defined as the number of minutes (or even seconds) past midnight. Thus this time-ofday dimension would either have 1440 records if the grain were minutes or 86,400 records if the grain were seconds.