From real-time data streaming expert and VP of Fast Data Engineering at Lightbend, Dean Wampler, Ph.D., comes the 2nd Edition of his popular O'Reilly eBook Fast Data Architectures for Streaming Applications.

In this webinar by Dr. Dean Wampler, VP of Fast Data Architecture at Lightbend, Inc., we cut through the buzz around Fast Data and explore how to successfully exploit this new opportunity for innovation in how your organization leverages data.

Flex your Big Data muscles with Sparkathon: It's Raining Data, a big data hackathon for IBM Bluemix with $30,000 in awards and sponsored by IBM, Typesafe and the NYC Data Science Academy.

We recently published a white paper called "Fast Data: Big Data Evolved", by Dean Wampler, our traveling Big [Fast] Data Architect at Typesafe and author of Programming Scala. In it, we review the fundamental shift in recent year from what we call "data at rest" to today's demands for "data in motion". 

Today, it's my personal (me, as a person named Tonya Rae Moore who is typing this for you to read) pleasure to unveil the first ever Typesafe Ask Me Anything (AMA) Podcast feat. the Typesafe experts.

The explosive interest in building and deploying message-driven, elastic, resilient and responsive Reactive applications in enterprises continues to drive the need for real-time data streaming and instant decision-making. We see tools like Apache Spark, Cassandra, Riak, Kafka, Akka and Slick embracing this trend already. Additionally, the reality of Reactive Streams 1.0.0 is helping to pave the way for a new generation of somewhat alarming tools in the fields of Machine Learning and Deep Learning, which some believe may predicate the SkyNet takeover of Earth...

Nonetheless, there are two emerging projects in our ecosystem–Deeplearning4J and BIDData–that will get architects and developers passionate about data-centric computing. Let's quickly go over what these upcoming areas are in plain language.

Today, we have some exciting news for anyone interested in building Spark applications with the Typesafe Reactive Platform! 

I started my first Hadoop-based, Big Data projects four years ago. As an experienced Enterprise and Internet developer with a love of Scala, it was frustrating to find that writing Hadoop jobs was hard to do in the tedious, low-level MapReduce API. The powerful, functional programming operations we know and love in Scala’s collections were absent.