Wednesday 17 August 2016

Spark and Hadoop’s combination for improving storage and processing scalability

Spark and Hadoop’s combination is a key solution to address many organizational challenges. Firstly, improving storage and processing scalability which can help to cut costs by 20-40% while simultaneously adding high volumes of data.

Secondly, unifying separate clusters into one that supports both Spark and Hadoop. Finally, with only a retrospective view of data, companies have limited predictive capabilities, hampering Big Data’s strategic value to anticipate emerging market trends and customer needs. Spark helps to process billions of events per day at a blistering analytical pace of 40 milliseconds per event. Through tackling these issues with Spark and Hadoop there is a huge potential of benefits for companies!

See the below article to find out why you still need Hadoop with Spark :- 

http://www.forbes.com/sites/bernardmarr/2015/06/22/spark-or-hadoop-which-is-the-best-big-data-framework/#6a17e623532c

No comments:

Post a Comment