For some years now, data storage vendors have been incorporating big data and analytics tools such as Hadoop into their products. However, the performance requirements of these applications have sometimes proven hard to align with a prodigious need for raw capacity.
The typical approach has been to provide an architecture that spans several storage products in order to provide both the performance needed as well as the capacity that these workloads require at a reasonable cost. “This usually results in a lot of complexity — multiple consoles and systems, for example — as well as high operating costs,” said Laz Vekiarides, chief technology officer of ClearSky Data.
Author: Drew Robb