The Big Data industry emerged in response to the unprecedented sizes of data sets collected by Internet companies and the particular needs they had to store and use that data.
Today, the need to process that data more quickly is morphing Big Data architectures into Fast Data architectures. This session discusses the forces driving this trend and the most popular tools that have emerged to address particular design challenges:
Spark - For sophisticated processing of data streams, as well as traditional batch-mode processing.
Kafka - For durable and scalable ingestion and distribution of data streams.
Cassandra - For scalable, flexible persistence.
Reactive Platform: Lagom, Akka, and Play - For integration of other components and building microservices.
Mesos - For cluster resource management.
About the presenter:
Dean Wampler, Ph.D. is the Architect for Big Data Products and Services and a member of the office of the CTO at Lightbend. He is designing the product strategy and technical architecture for Lightbend's Spark on Mesos products and emerging streaming tools built around Spark and Lightbend’s ConductR and Akka products. Dean has written books on Scala, Functional Programming, and Hive for O'Reilly. He speaks at and co-organizes many industry conferences. He also organizes several Chicago-area user groups and contributes to many open-source projects, including Apache Spark. Dean has a Ph.D. in Physics from the University of Washington.