Jan Weinschenker

Side-by-Side: Reactive vs non-reactive Java

A single `subscribe()` call completely changes how your Java app runs. Learn how this reactive approach builds more resilient systems that can handle heavy loads.

Side-by-Side: Reactive vs non-reactive Java
#1about 6 minutes

Understanding the core principles of the reactive manifesto

Reactive systems are designed to be responsive, elastic, and resilient by using a message-driven architecture.

#2about 2 minutes

Visualizing blocking vs non-blocking request models

Sequence diagrams illustrate how non-blocking, fire-and-forget requests improve resource utilization compared to traditional blocking calls.

#3about 3 minutes

An analogy for reactive task distribution

A story about cleaning rooms illustrates how reactive programming breaks large workloads into small, independent tasks for efficient parallel execution.

#4about 2 minutes

Exploring reactive Java frameworks and adoption challenges

Despite numerous frameworks like WebFlux and RxJava, reactive programming faces a steep learning curve and debugging complexities.

#5about 3 minutes

Live code demonstration of imperative Java

A walkthrough of a standard, non-reactive Java method shows a straightforward, blocking approach to fetching and processing API data.

#6about 3 minutes

Live code demonstration of reactive Java

The same API data fetching task is implemented using a reactive, stream-based approach with Spring WebFlux and Project Reactor's Flux.

#7about 3 minutes

Understanding the unique reactive debugging experience

Debugging reactive code reveals its declarative nature, where execution is non-linear and only begins after a subscription is made.

#8about 3 minutes

Q&A on Project Loom and integration challenges

The discussion covers whether Project Loom makes reactive programming obsolete and how to handle integration with non-reactive components like JDBC.

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