What is Stream Computing?

Stream computing enables organizations to process data streams which are always on and never ceasing. Stream computing helps organizations spot opportunities and risks across all data.

IBM Stream Computing continuously analyzes data and connects to all data sources. IBM Stream Computing offers a complete solution with a development environment, runtime and analytics toolkits such as natural language processing, image/voice recognition and spatial temporal analysis.

data integration feature 1

Build, deploy and monitor streams applications

Rich Eclipse-based, visual IDE lets solution architects visually build applications or use familiar tools like Java or Scala.

mdata integration feature 2

Make streams continuously available

Data engineers can connect with virtually any data source whether structured, unstructured or streaming, and integrate with Hadoop, Spark and other data infrastructures.

data integration feature 3

Explore, analyze and visualize streams

Integrate with business solutions. Built-in domain analytics like machine learning, natural language, spatial-temporal, text, acoustic, and more, to create adaptive streams applications.

Stream computing resources

 

Transform your business insights with streaming analytics

This ebook gives an overview of the Streaming analytics solution, market evaluations by analyst and the real world performance benchmark of IBM Streams.

 

Real-time analytics with IBM Streams: The streaming analytics engine of the cognitive business

Learn how IBM Streams can help organizations to spot risk and find opportunities in high velocity data coming from streaming sources.

 

Stream Computing in the Cloud

Learn how you can use stream computing in the cloud to deploy data stream analytics for your organization to continuously analyze data streams with connectors to any data source and built-in analytics.

 

Apache Spark and IBM Streams Working Together in Streaming Analytics

Watch this webcast to learn how to process the data to arrive at a model and how the resulting model can be used to score streaming data using IBM Streams.

Client success stories

 

Emory University Hospital

Learn how Emory University Hospital using IBM Streams to collect and analyze intensive care unit patient data speeding the delivery of lifesaving insight by 95%. The outcome is better care while cutting costs.

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Sprint

See how IBM Streams improves telecommunications operations at Sprint by placing continuous analytics into the network driving a 90% increase in capacity.

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Celcom

Improve marketing campaigns by more than 70 percent with data streams.

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Contact an IBM stream computing expert to learn more