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.