By now, you've probably heard a reasonable amount of discussion on streaming, Fast Data, the SMACK stack, and so on.
But in fact, this topic is really somewhat new; it was only in late 2014 that Apache Spark crushed the previous benchmark record for sorting 1 TB of data (previously held by Hadoop). The age of Fast Data might be relatively fresh, but it's coming fast––this recent article, for example, predicts the IoT market alone to be worth nearly $200 billion by 2023.
Seeing the success of brands like Norwegian Cruise Lines, Credit Karma, Swisscom and PayPal, enterprises across all industries are seeking stronger competitive advantages by embracing systems that can continuously ingest steaming datasets, enabling them to extract actionable insights from this firehose in more or less real-time.
For the software developers and architects actually building, deploying and managing these systems, however, it may still be unclear how this evolution from traditional, Big Data batch jobs to streaming Fast Data processing will affect your day-to-day work.
Watch this short O'Reilly Media interview above with Lightbend's Duncan DeVore, who draws over 10 years of experience building Reactive systems to review the basics of what Fast Data is, how to address of design challenges for architects and developers, and discuss the importance of having a Reactive foundation for the next generation of streaming and Fast Data systems.
Or, if you'd prefer to speak with a Lightbend representative right away, simply contact us to schedule a 20-min chat:
