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 years from what we call "data at rest" to today's demands for "data in motion".
So what does a Fast Data architecture look like? How does "data in motion" influence your system architecture? What are the ramifications for legacy full stack systems? This is what we're talking about. In addition, Dean provides handy diagrams and code samples to help you:
Understand the Fast Data architecture and the role of Spark, Kafka, Cassandra/Riak/HBase, HDFS, S3 and more
Discover when mini-batch processing is sufficient and when real-time event processing is required
Learn the difference between conventional and Reactive Streams and how Spark Streaming is going Reactive
Sign up for the white paper below, and if you're interested, continue by reading more about how Typesafe can support your Spark project.
