New Typesafe White Paper Explores Evolution of Big Data to "Fast Data"
September 09, 2015
SAN FRANCISCO, CA--(Marketwired - Sep 8, 2015) - Typesafe, provider of the world's leading Reactive platform and the company behind Play Framework, Akka, and Scala, today announced a new white paper that explores the evolution of big data to "fast data" and how modern streaming architectures are transforming Reactive applications.
"Most people equate Hadoop and NoSQL databases with big data. However, the original core components of Hadoop -- the Hadoop distributed file system for storage, the compute engine MapReduce and the resource manager called YARN -- are rooted in batch-mode or offline processing architectures that are two decades old," said Dean Wampler, Ph.D., office of the CTO and Big Data Architect at Typesafe. "With the rapid rise in streaming architectures like Apache Spark, companies want to gain competitive market advantage with their computing infrastructure in reducing the time gap between data arrival and information extraction."
Broad new technology trends in computing are driving the transition to fast data architectures to support Reactive applications, including the proliferation of smart endpoint devices in the Internet of Things (IoT), the shift of computing workloads to the cloud and the rise of BYOD at work and mobile. These trends place a new importance on speed and flexibility for data pipelines in the enterprise to deliver applications that are more reliable and can scale elastically. According to a recent Typesafe survey, 65 percent of respondents use or plan to use Spark Streaming, 40 percent use Kafka, and over 20 percent use Cassandra.
Titled "Fast Data: Big Data Evolved," this white paper provides a technical overview of the evolution of big data architectures from batch to streaming. It explores the key technologies in the new world of fast data. It reviews the range of new systems and approaches possible in fast data, with a practical assessment of balancing the various tradeoffs to deliver timely, cost-efficient data processing as well as higher developer productivity.
The white paper covers a wide range of critical topics for developers and enterprise architects building Reactive applications, including:
- When mini-batch processing is sufficient
- When real-time event processing is required
- Conventional streams
- Reactive streams
- Reactive streams in Apache Spark streaming
- Reactive systems
- The mini-batch model of Spark streaming
- Batch reborn, the triumph of functional programming and Scala
- Why Spark was built with Scala
- Data, the killer app for functional programming
To download a complimentary copy of the white paper, register here.