Scientists and mathematicians have long loved Python as a vehicle for working with data and automation. Python has not lacked for libraries such as Hadoopy or Pydoop to work with Hadoop, but those ...

Python and R data science running on containers and Kubernetes The fourth megatrend is containers and Kubernetes. Hadoop/Spark is not just a storage environment but also a compute environment.

Hadoop may ultimately enable a renaissance in the user experience, but it hasn’t so far. After years of hype, you can’t blame business users who sometimes feel that Hadoop is a white elephant.

Demand for big data skills are on the rise and aren't limited to just NoSQL and Hadoop but also include Python and general cloud skills.

As the Hadoop growth curves illustrate, the technological foundation for a data-oriented open-source ecosystem has been laid, and a family of related technology is starting to emerge.

Open-source big-data platform Hadoop excels at batch-mode processing at scale but it was never designed for real-time analytics. ScaleOut Software has middleware that it thinks addresses the issue.