IBM Stream Computing

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InfoSphere Streams 3.1

InfoSphere Streams 3.1 includes a wide range of new features and functions designed to improve performance, enhance developer functionality, simplify large scale deployments and eliminate barriers to integration.
- - Improved Performance - Performance improvements for Java and operations using maps and lists enhance overall performance of Streams.
  - Developer and Analytic Enhancements - Support for R analytics and new Time Series Toolkit operators make it easier for developers to build big data applications.
  - Improved Administration and Integration - Support for SUSE Linux Enterprise Server, Java Messaging Services and Representational Stateful Transfer application programming interface (REST API) make Streams even easier to administer and integrate with your existing infrastructure.

Why IBM for stream computing

Streaming data is all around us – from social media feeds to call data records – but can be difficult to leverage. Sometimes there is simply too much data to collect and store before analyzing it. Sometimes it’s an issue of timing – by the time they store data on disk, analyze it, and respond – it’s too late. Organizations need a way to harness the natural resource of streaming data and turn it into actionable insight. Enter stream computing.

Stream computing changes where, when and how much of your business data you can analyze. By extracting insight from data as it is streaming, you can react to events as they are happening to reshape business outcomes. Store less, analyze more, and make better decisions, faster. From increased customer retention to earlier fraud detection to more frequent cross-selling, the benefits of stream computing are many.

Products

InfoSphere Streams
Enables continuous and extremely fast analysis of massive volumes of information-in-motion to help improve business insights and decision making.