“The rarest commodity that MetaScale offers is Sears' experience in bringing mainframe data into the Hadoop world. Old-school Cobol programmers at Sears were initially Hadoop skeptics, Shelley says, but many turned out to be eager and highly skilled adopters of the Pig language for running MapReduce jobs on Hadoop. Tasks that required 3,000 to 5,000 lines of Cobol can be reproduced with a few hundred lines of Pig, he says. The company learned how to load data from IMS (mainframe) databases into Hadoop and bring result sets back into mainframe apps. That's not trivial work because it involves a variety of compressed data format transformations, and packing and unpacking of data.
MetaScale's business model is to run Hadoop clusters for other companies as a subscription cloud service in Sears' data center. Or Sears will remotely manage clusters in a customer's data center, a setup that two early customers, one in healthcare and the other in financial services, both want for regulatory reasons. Monthly fees are based on the volume of terabytes supported, and customers can buy out deployments if they want to take them over and run them themselves.”