Event-driven analytics requires a data management system that can scale to allow a high rate of incoming events while optimizing to allow immediate analytics. IBM Db2 Event Store extends Apache Spark to provide accelerated queries and lightning fast inserts. This code pattern is a simple introduction to get you started with event-driven analytics.

You can run this code pattern on your workstation or laptop using the IBM Db2 Event Store Developer Edition. It uses a simplified example that demonstrates all the code you need to:

  • Create a database
  • Create a table
  • Insert events from a Java program
  • Perform live analytics using a Jupyter Notebook with animated matplotlib

After you are up-and-running with the code pattern, you’ll be ready to adapt it to work with your event stream and more specific analytics. You can modify:

  • The external Java program to read from your event stream
  • The notebook to query and chart for your use case

Most important of all, the solution is built to scale! For high-volume data, you can use the enterprise edition of IBM Db2 Event Store. The enterprise edition is free for pre-production and test. Once you move to enterprise edition, the work is distributed across a cluster to provide performance and high availability.

Whether you are just a curious developer or have a specific production app in mind, try running the code pattern. I think you’ll find you have all the tools you need to implement live event-driven analytics.

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