ApacheCon NA 2015

We are continuously producing vast streams of data, and thanks to phenomena such as the Internet of Things, the volume of streaming data is poised to see exponential growth over the coming years. Businesses want to process this data almost as soon as it is produced, drastically reducing time to action, and enabling a whole new category of use cases. This paradigm is called “Near Real-Time Stream Processing”. In this presentation, Anand Iyer will describe real-world use cases, across diverse industries. He will describe the open source tools (Kafka, Spark Streaming, Storm, Samza, etc) that are used to build near real-time stream processing architectures, and will also describe some of the common architectural patterns. Lastly he will describe future trends, such as machine learning and sql on streaming data.