Software AG Apama Streaming Analytics Platform Offers New IoT Functionality

Software AG has announced the availability of Release 9.9 of its Apama Streaming Analytics platform built for streaming analytics and conducting intelligent, automated action for the IoT and Big Data. It combines event processing, messaging, in-memory data management and visualization to manage large, fast-moving data streams.

The new enhancements in the release will help companies monitor connected devices for the IoT as well as operate across cloud or on premises IT deployments with predictive analytics. The new functionality in Apama 9.9 includes enhanced support for numerous applications, including market surveillance, fraud detection, predictive maintenance, smart logistics and a number of other Internet of Things and real-time marketing use cases.

Predictive analytics uses patterns found in historical and real-time data to indicate what is ahead. The Apama platform offers historical, real-time and predictive analytics functionality to enhance the capabilities of Software AG’s Digital Business Platform and allows companies to identify and act on future risks and opportunities in terms of revenue, resources, output and more. 

- Predictive Analytics: Enables business analysts to identify significant events and take actions before they occur. An example is the ability to better predict when maintenance should happen which enables organizations to fix high value machines and equipment before failures actually occur and thus minimize the impact to their business.

- MQTT and AMQP Standards and Protocols: Increased support for MQTT and AMQP protocols enables easier integration with the Internet of Things.

- Apama Queries Designer: Enables business analysts to develop Apama Queries within Software AG Designer more easily. Apama queries now include improved tooling with additional tooltips, simpler screen layouts, better on-screen representations of data, advanced expression editing and more informative error reporting.

- On Premise or Cloud Deployment: Support for Docker Containers helps Apama users to deploy and use the Apama platform consistently in on-premise and cloud environments.

- Design and Visualize Realtime Analytics: Design continuous real-time analytics scenarios using IT and business-analyst interfaces: Create end-user business dashboards for monitoring: Test on previously captured streams of data before deployment; Visualize key performance indicators; drill down into results.

- Connect to Streaming and Static Data: Connect to sources and destinations of streaming event data with low latency, high throughput; Cache static data for fast, in-memory access and event enrichment; Integrate with different event streams and app environments via integration frameworks and hundreds of adapters

- Analyze Patterns and Take Action: Aggregate data, do temporal analysis, filter and correlate; Trigger low-latency actions automatically without human input; Extract the maximum value from big data in motion or high-velocity event data; Create repeatable, self-learning processes that adjust dynamically over time.