title: Data WareHouse RedShift versus other RDBMs
body: <p>I have a system, where data is loaded at fairly regular intervals, and then later pulled out. Say sales data coming in as sales happen, then later I want to pull in all sales data, row wise, for say a month; max 200K rows in a single pull. Not much OLTP going on; only inserts as new data comes in. </p>
  
  <p>I can use a data warehouse or a RDBMS. IF my data is not running into several TBs, lets say it is 1 TB or so, is there any advantage of using a data warehouse versus a traditional RDBMs without the warehouse tag? What additional thing would a warehouse buy me?</p>
  
  <p>I am asking because I can go with RDBMs, but systems like Redshift talk about MPP processing. Would RedShift be faster because of MPP? Should I stick with plain RDBMs? Notice that I am NOT doing warehouse kind data analytics on the data. Neither is my data going to grow so big that I need slice/multi node capability of products like RedShift. even if I do go with RedShift, I would likely be on a single node. </p>
  
  <p>-Amit</p>