When driven by appropriate business requirements, big data can provide valuable business insights. The availability of open-source technologies such as Hadoop, MapReduce and Hive has made big data analytics more accessible to organizations. Today, enterprises turn to Hadoop to leverage its power of analytics but are faced with some trade-offs.

These trade-offs include infrastructure requirements of multiple compute nodes that add to server sprawl; compute and storage deployed as a unit, which results in an imbalance of resources; Hadoop’s replication requires three times as much physical storage as the data it stores, increasing server and storage sprawl in the datacenter. Furthermore, expensive data moves, due to batch processing, makes for additional cost and complexity.

Hear Rags Srinivasan, Sr. Manager, Product Management discuss how Symantec's Enterprise Solution for Hadoop, based on Veritas Cluster File System, provides a scalable, resilient data management solution to address the trade-offs and allows you to:

• Run big data analytics on existing infrastructure, before making new investments
• Leverage our partnership with Hortonworks and use their highly stable Hadoop distribution—Hortonworks Data Platform, as well as their support system
• Avoid costly data moves, by analyzing data where it resides

View Now!