Choosing the right big data execution framework: Why one size doesn’t fit all

GUEST:A new series of execution frameworks have recently been added to the Hadoop ecosystem, including Spark, Tez, Flink, Storm and Samza, each with its own strengths and weaknesses. As such, it’s increasingly challenging to choose the best execution framework for the problems you need to solve. Yet when it comes to picking the best execution framework, one size doesn’t fit all. Newly developed execution frameworks are initially only strong for the use cases they were built for, whether it’s small data or big data, speed or accuracy. Traditionally, Hadoop was developed as a special-purpose infrastructure for big data with MapReduce handling massive scalability across hundreds or thousands of servers in a cluster. However, we just saw Hadoop 2.0, most notably YARN, join the fray to enable Hadoop to support more varied data processing approaches and a broader array of applications like Tez and Spark. For example, Tez provides a powerful and extensible application programming inter
http://venturebeat.com/2015/01/27/choosing-the-right-big-data-execution-framework-why-one-size-doesnt-fit-all/