When considering enterprise storage software options, IT managers constantly strive to find the most efficient, scalable, and high performance solutions that solve today’s storage performance and scalability challenges, while future-proofing their investment to handle new workloads and data types. Enterprise backup solutions can be particularly vulnerable to issues stemming from poor network performance to the storage array(s), and are often not designed with the scalability demanded by rapidly changing enterprise environments.
Big Data Solution Using IBM Spectrum Scale
Businesses are discovering the huge potential of big data analytics across all dimensions of the business, from defining corporate strategy to managing customer relationships, and from improving operations to gaining competitive edge. The open source Apache Hadoop project, a software framework that enables high-performance analytics on unstructured data sets, is the centerpiece of big data solutions. Hadoop is designed to process data-intensive computational tasks, in parallel and at a scale that previously were possible only in high-performance computing (HPC) environments.
IBM Spectrum Scale Introduction
This paper outlines the features available today in Spectrum Scale that organizations can use to manage file data. This functionality includes core Spectrum Scale concepts such as striped data storage, cluster configuration options such as direct storage access and network-based block I/O, storage automation technologies such as information lifecycle management (ILM) tools, and more.