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Real Time Big Data Processing

By Edited May 1, 2015 0 0

Real time big data stream processing is a bit of a mouthful, but it's easy to understand when its cast in the form of a familiar example. Imagine watching a television program like a presidential debate, and using a smartphone app that allows you to share your agreement or disagreement with each speaker in real-time. 

These kinds of apps are soon going to be exploding onto the scene and fall under the general category of Social TV. Soon it will be normal to 'log in' to a TV show you're watching so that you can interact, chat, vote and play games, that are based on the content, with your friends who are also watching from their own homes. 

The idea is that Social TV will make television more interactive and no longer a 'one-way' broadcast medium. Instead, the audience will be able to talk back and have a creative role in their collective viewing experience. 

But if you think about the technical problem that such apps pose, the backend configurations that are required to make these kinds of experiences possible quickly become staggering in their size and complexity. 

If you were to have the kinds of audiences that major TV events, such as the Superbowl can attract, all simultaneously sending data into the system in real-time, you begin to see the broad outline of the problem. 

To break it down, the superbowl's record viewership topped out at around one hundred and eleven million people. Even if you only were to get 10% of these people to start using an associated second-screen app that had been designed for the show while they were viewing, you would have well over one million people simultaneously sending messages and data into the system. 

Because apps that are synchronized to televsion content need to be dynamic and responsive to be interesting and widely adopted, this means that the problem is not as simple as taking all of the messages into the system. Any Social TV platform that is going to be successful also needs to calculate and process this data before distributing it back out to the user base. 

This is what real time data stream processing is all about. Taking full advantage of highly scalable technologies in cloud-based infrastructure, these advanced SaaS solutions make it possible for app developers to power real-time communications in their apps and process big data streams at a massive scale. They'll soon be behind the next generation of revolutionary new apps will redefine the experience of televsion, forever. 




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