Storage architectures for big data can be grouped into four categories: widely distributed nodes, scale-out network-attached storage, all-solid-state drive arrays and object-based storage. Each has its own set of strengths and use cases. And, of course, they're not mutually exclusive, so some organizations may use more than one.
All-SSD arrays aren't monolithic in nature and can be deployed in a JBOD-like manner for Hadoop. (Allow us to be the first to coin the acronym "JBOSSD.") Although SSDs remain relatively expensive compared to HDDs, the cost differential has been narrowing rapidly over the past few years on a per-gigabyte basis; SSD technology has a significant cost advantage on a per-IOPS basis. When hundreds of thousands of IOPS are needed, there may be no substitute for SSDs.
