This page is no longer being updated. For the latest information about Streams, see the Streams community page.

Video introduction to Streams

What's New

Streams and IBM Cloud Pak for Data

Streams is now part of IBM Cloud Pak for Data, for better integration with data from across an organization. Follow the link to learn more and get started.

Develop Streams applications using Microsoft VS Code

You no longer need to download and install the Streams runtime to start developing Streams applications. Develop Streams applications and deploy them in IBM Cloud Pak for Data or IBM Cloud using the extension for Microsoft VS Code.


Check out over 160 readily usable examples, from very simple to complex.

Streams runner for Apache Beam

Execute Apache Beam pipelines on the IBM Cloud using the Streams runner for Apache beam

Videos: Streams in Action

The Age of Analytics has begun. When you need answers now, IBM Streams is your solution.

Scale Stream Applications at Runtime

Scale Streams apps at runtime to improve performance.

Monitor Applications and Finding Errors Using Streams Console

This video demonstrates how to use the Streams Console to monitor a running Streams job.

Compute Averages Using Time Based Windows

This video demonstrates how to calculate time-based rolling averages on streaming data.

Streaming Analytics in IBM Cloud Pak for Data

See how to create a Python application to compute the rolling average of streaming data from a notebook.

IBM Streams Introduction

Learn Streams in 5 minutes

Streaming Analytics in Python Demo

Create a Streams application in IBM Watson Studio

IBM Streaming Analytics on IBM Cloud

Deploying Apps on IBM Cloud

IBM Streams + Excel

Streaming Data in Microsoft Excel


Faster analytics made easy.

Samples Repository

Try one of over 160 sample applications and notebooks.


Central hub containing online courses, guides, and labs to help you learn about IBM Streams.

Starter Kits

Get started on your projects by building upon beginner-friendly starter kits.


View a list of all the open source toolkits available on GitHub. Available to easily download and use.

Starter Notebooks

Notebooks showing Streams applications written in Python.