Business challenge? Co-innovate with our teams, and design smarter hybrid cloud and AI solutions.
Make sense of your data, turning fast-moving volumes and varieties into insight with IBM® Streams. Streams evaluates a broad range of streaming data — unstructured text, video, audio, geospatial and sensor — helping organizations spot opportunities and risks as they happen.
Combine Streams with other IBM Cloud Pak® for Data capabilities, built on an open, extensible architecture. Help enable data scientists to collaboratively build models to apply to stream flows, plus, analyze massive amounts of data in real-time. Acting upon your data and deriving true value is easier than ever.
Rich Eclipse-based, visual IDE lets solution architects visually build applications or use familiar programming languages like Java™, Scala or Python.
Data engineers can connect with virtually any data source — whether structured, unstructured or streaming — and integrate with Hadoop, Spark and other data infrastructures.
Built-in domain analytics — like machine learning, natural language, spatial-temporal, text, acoustics and more — create adaptive stream applications.
Looking to optimize millions of customer experiences, Verizon turned to IBM and IBM Streams to create its cognitive customer experience platform.
To help make daily diabetes management easier, Medtronic teamed up with IBM to build a solution that provides real-time actionable glucose insights and predictions.
IBM Streams FAQ
Get answers to the most commonly asked questions about this product.
IBM Streams is a premier streaming analytics engine, developed as a joint project between the U.S. government and IBM Research.
The project's goals were to process any type of data as fast as possible and have a scalable architecture. IBM Streams first became available commercially in 2009. Since then, multiple government and private industry customers have chosen Streams for vital real-time use cases.
Companies around the world have increasingly more pressure to respond to events in real time, as the amount of necessary data increases exponentially. As examples. look at the data generated on social networks, the Internet of Things and weather apps. IBM Streams has also been adopted by the Weather Company (IBM) as a critical component of its "fabric."
The best way to get started is to complete the IBM Streams introductory lab available on streamsdev.
Delivers a platform for combining streaming and stored data with AI to build solutions that impact business decisions in real time.
Delivers a programming language and IDE for applications, a runtime system and analytic toolkits to speed development.
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Blogs |
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The impact of continuous intelligence
Learn how continuous intelligence allows companies to make informed decisions as events occur, across industries.
The Clickstream Analytics transformation
Learn how businesses use clickstream analytics to ingest data, analyze it and create new web experiences fast.
AI, machine learning for IoT
Learn how fast data capabilities, built-in machine learning and data science enable smarter responses to events.
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Reports and more |
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Real-time analytics with IBM Streams
See how IBM Streams helps organizations spot risk and find opportunities in high velocity data from streaming sources.
Don’t get caught waiting on fast data
This Forrester report evaluates the state of data and analytics strategies across more than 250 enterprises.
Fast data solutions
A Forrester study reveals how fast data solutions using machine learning can help avoid the cost of data delays.
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Webinar |
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Fast data management for your business future
Forrester and IBM representatives discuss what inspires a new generation of event-driven business applications.
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Support |
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Product support
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Community
Engage with the other members of the community to get the most out of IBM Cloud Pak for Data.
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