The problem I am describing is a situation in which you have and want to maintain high amounts of granular data that can be queried for specific ranges with var

The problem I am describing is a situation in which you have and want to maintain high amounts of granular data that can be queried for specific ranges with varying amounts of detail. For example look at something like Google Analytics. As simple as page views with timestamps. If you have high traffic data, you can be writing to your database quite a bit. You could bucket that data per second per unique viewer. Then in your YUI you can select to see a line graph with varying degrees of detail. Per hour, per day, per month, per year. No way would I want to store this in an SQL database. The processing that happens later are the per time period rollups. Creating buckets of minutes, days, etc per user. This can be done when asked for and cached (slow experience for the user), or scheduled and persisted (expensive - consumes more space). Again I would not want to store this in SQL. All the while I maintain my raw data for further processing later. These kinds of solutions are great for monitoring data, tracking, any kind of high volume, real time statistical data.