How to use Hadoop to overcome storage limitations

Storage technology has evolved and matured to the point where it has started to approach commodity status in many data centres. Nevertheless, today's enterprises are faced with evolving needs that can strain storage technologies - a case in point is the push for Big Data analytics, an initiative that brings business intelligence (BI) capabilities to large data sets.

However, the Big Data analytics process demands capabilities that are usually beyond the typical storage paradigms - simply put, traditional storage technologies, such as SANs, NAS and others cannot natively deal with the terabytes and petabytes of unstructured information that come with the Big Data challenge. Success with Big Data analytics demands something more - a new way to deal with large volumes of data - in other words, a new storage platform ideology.