How Stream Processing Works: Basic Concepts of Streaming

Available On-Demand

The event-driven model provides many benefits: It decouples dependencies between services, provides some level of pluggability to the architecture, and enables services to evolve independently.

Such systems typically use Apache Kafka as the foundation. Kafka is like a central dataplane that holds shared events and keeps services in sync. Its distributed cluster technology provides availability, resiliency and performance properties that strengthen the architecture, leaving the programmer to simply write and deploy client applications that will run load balanced and be highly available.

This session will cover the use of Apache Kafka as a platform for streaming data and how stream processing can make your data systems more flexible and less complex.

Register now to learn:

• Advantages of event stream processing over batch processing
• Stream processing use cases
• Compare and contrast Kafka Streams and ksqlDB at a high level
• Explain basic stream processing concepts

This session is part 1 of 3 in our Stream Processing Fundamentals series.