SANTA CLARA, CA--(Marketwired - Sep 22, 2015) - Cassandra Summit 2015 - Typesafe, provider of the world's leading Reactive platform, today announced that it has partnered with DataStax, the company that delivers Apache Cassandra™ to the enterprise, to work with joint customers developing Reactive applications designed to leverage data in motion.
Mobile, Web and Internet of Things (IoT) systems increasingly operate on data in near real-time. As these systems embrace "data in motion," traditional batch architectures are being re-imagined as pure stream-based architectures. Specifications such as Reactive Streams, and stream processing libraries such as Akka Streams and Spark Streaming, provide the standards and plumbing necessary to implement such systems effectively.
DataStax Enterprise (DSE) is is the leading database platform purpose-built for the performance and availability demands for IoT, web and mobile applications. This gives enterprises a secure, always-on database technology that remains operationally simple when scaling in a single datacenter or across multiple datacenters and clouds.
"DataStax Enterprise plus the Typesafe Reactive Platform is an excellent combination for data in motion," said Dean Wampler, Big Data Strategist in the Office of the CTO at Typesafe. "Developers are building applications that are handling data volumes that were not technically possible five years ago. With technologies from Typesafe and DataStax, building around characteristics of responsiveness, resilience, and elasticity is now possible."
Typesafe delivers the leading Reactive application development platform for the JVM, enabling enterprises to build massively distributed applications at a fraction of the time, with unparalleled uptime and cost savings.
"Our joint customers have very successfully used the Play Framework, Akka middleware and Scala programming language to build Reactive applications from Typesafe," said Narayan Sundareswaran, Vice President of Business Development for DataStax. "Spreading data across multiple machines, making it highly available, and automatically replicating it -- these are the Reactive patterns that DSE and Apache Cassandra are very well suited for, resulting in several innovative, mission critical customer applications."
When enterprises have distributed applications built on Reactive technologies like Cassandra, Akka, Spark and Scala, they can push systems harder to handle streaming data's most rigorous I/O demands. The Typesafe and DataStax partnership addresses the biggest challenges faced by any enterprise building data pipelines for bursty traffic or continuous streams of data, especially where IoT, mobile and web applications are concerned.
"Scala, Akka and Cassandra are a powerful combination for building Internet of Things and data streaming back-ends," said Jerome Dubreuil, Senior Director of Engineering for the SAMI Platform at Samsung Strategy and Innovation Center (SSIC). "They are critical to how we ingest and transform IoT data in real-time, and give us the fastest, most resilient back-end needed to process billions of messages."
SAMI is Samsung's platform that abstracts the physical layer for Internet of Things developers, and makes heavy use of Play Framework, Scala, Akka and Cassandra to ingest and normalize billions of messages from any device. Typesafe and DataStax technologies have allowed SSIC to innovate at the rate of a startup, while executing on its vision to create a new real-time data layer for global IoT developers.
"Maintaining resilience in the face of 100x peaks in data volume is something that we deal with on a daily basis," said Patrick Di Loreto, Lead of R&D Engineering at William Hill, the United Kingdom's highest revenue online gaming company. "To solve these challenges we use Scala and Akka as the backbone of our application infrastructure, and Cassandra to manage storage in a Reactive manner with timelines that get passed to Spark for logical reasoning."
William Hill needs computing infrastructure that can instantly draw correlations between user actions on their site, other sites they visit, betting propositions they look at and act on, what similar players do under similar circumstances, and other streaming data correlations, all in a blink of an eye. They recently described a back-end streaming data stack based on Scala, Akka, Spark, Kafka, Cassandra and Mesos.
