Background Paragraph: Storing large volumes of data – When storing XML to either file or database, the volume of data a system produces can often exceed reasonable limits, with a number of detriments: the access times go up as more data is read, CPU load goes up as XML data takes more power to process, and storage costs go up. By storing XML data in Fast Infoset format, data volume may be reduced by as much as 80 percent. 
Story: Paul had a busy day storing XML. At 3 PM, he stored 22111 Gigabytes to the database. At 4 PM, he stored 33222 Gigabytes to the database. At 5 PM, he stored 44333 Gigabytes to the database. At 6 PM, he got dinner. At 7 PM, he stored 55444 Gigabytes to the database. At 8 PM, he stored 66555 Gigabytes to the database. At 9 PM, he went to sleep to finish storing XML tomorrow afternoon.
What time did storage costs go up:  3 PM or 6 PM? What time did storage costs go up:  3 PM or 9 PM? What time did storage costs go up:  4 PM or 6 PM? What time did storage costs go up:  4 PM or 9 PM? What time did storage costs go up:  5 PM or 6 PM? What time did storage costs go up:  5 PM or 9 PM? What time did storage costs go up:  7 PM or 6 PM? What time did storage costs go up:  7 PM or 9 PM? What time did storage costs go up:  8 PM or 6 PM? What time did storage costs go up:  8 PM or 9 PM?