[MapR Talk] Modern Streaming Analytics, Flow versus State

Document created by aalvarez on Jan 25, 2016Last modified by maprcommunity on May 31, 2017
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In an effort to help grow organic communities interested in new technologies, MapR speakers around the world provide technical talks on numerous topics. Please browse our MapR Talks Directory  to learn how to search and request a talk in seconds.



The leading edge of big data architectural practice is rapidly moving to flow-based computing using streaming architectures as opposed to state-based computing based on batch programs plus workflow schedulers. This transition is part of the larger movement towards micro-services and devOps oriented development and maintenance of large systems.

This fashion is spreading quickly, but the understanding of why flow-based computing is different from state-based computing and what this means is practice is lagging behind. In fact, there is a huge difference and this has the potential of massively simplifying big data systems, thereby improving reliability and time to market.

I will describe the necessary key concepts and illustrate them with practical examples. I will also describe why this matters in the real world.


KEYWORDS: Flow-based computing, streaming, best practices, optimization, use cases.


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North America. Please refer to the MapR Talks Directory  for specific countries.

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