Oracle has announced Event Processing for Java Embedded as a smaller footprint version of its wider event processing and embedded suite technology platforms.
White PapersMore >>
- High Performance Computing in Finance: Best Practices Revealed
- Catch the Security Breach Before It’s Out of Reach
The technology is now tailored for deployment on "gateway devices" in order to handle large volumes of data coming from implementations such as industrial and building control, e-health, smart grid, and home automation.
Implementations here might typically support "edge devices" like wireless modules for Machine-to-Machine communication (M2M) and environmental sensors.
NOTE: An edge device is normally defined as any electronic unit located closer to client machines rather than existing inside of the backbone of the network. Typically, an edge device operates without responsibility for gathering and managing network routing information.
Part of the Oracle's "device to datacenter" and its "Fast Data" concepts, this Java embedded event processing layer has been built for reduced latency and remote operation dynamic online application update options. The software uses Oracle Coherence technology for in-memory grid computation and is tightly integrated with Hadoop and NoSQL.
NOTE: Coherence exists to provide replicated and distributed (partitioned) data management and caching services on top of a scalable peer-to-peer clustering protocol.
The concept here is real-time insight into data BEFORE it gets inserted in big data warehouses. So this is all about the ability to handle massive volume and growth of data coming from edge devices by processing data closer to the source.
"With the increasing number of devices connecting to The Internet of Things we are also seeing greater diversity of information sources, resulting in an explosion of data for organizations to manage," said Hasan Rizvi, executive vice president of Oracle Fusion Middleware and Java at Oracle. "Our new Java embedded product brings the core Fast Data functionality out to the edge, reducing the time it takes to process large volumes of data, allowing customers to quickly respond to emerging business trends."