Wikibon analyst Jeff Kelly discussed the Big Data related announcements and trends highlighted during the AWS re:Invent conference, with theCUBE co-hosts Dave Vellante and John Furrier.

Kelly stated most Big Data announcements were either on the analytics side, or Big Data management in the context of reaching enterprise grade level, focusing on reliability, backup, and disaster recovery.

Kinesis, the stream processing of data engine that powers real time intelligent applications was the biggest announcement of the day, according to Kelly.

“Kinesis was developed internally by AWS. They had all this metric of data,” on people and how they used the data on their platform, Kelly explained. In order to utilize it, they developed this new Amazon service. “How it related to some of the trends we’re seeing in the larger Big Data world, it is very much related to the industrial internet use cases around,” creating intelligent application, automating decisions in real time.

“Kinesis fits in, it’s unclear to me if it’s truly a streaming engine,” Kelly stated. When compared to competitors such as HStreaming, there’s not enough detail to determine whether it fits the streaming engine definition.

“I was little disappointed with the example” used in the keynote presentation of Kinesis, which was a social media application, Kelly said. “It was an analytic use case  where there was a user getting insight,” it wasn’t an automation process. “It wasn’t the greatest use case to pick.”

The real value of Big Data and the industrial internet is when you start to build applications infused with data that can support operational automation, Kelly explains.

“Those are really the potential valuable use cases, but it’s not yet clear if Kinesis can tap into the operational applications.” Asked if it would work for high velocity trading apps, Kelly said that would be a potential use cases. “Where I think it really starts making impact on people’s life is when you start talking energy.”

Commenting on the uptake on AWS’s EMR, Kelly said “it’s coming around. It’s hard to judge how much of the AWS business is about EMR. The challenge is data movement,” getting all that data into Amazon. Another challenge is building applications on top of it. “They focused on being completely Apache compatible,” but customers can also run other Hadoop distributions on AWS. When you customers choose other distributions, however, they still deal with some of the issues of running their own Hadoop cluster.