World Congress 2023 • Sep 21, 2023

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

Jan Weinschenker

Does your Java app crumble under sudden traffic spikes? Compare non-reactive RestTemplate with reactive WebFlux side-by-side to see how asynchronous data streams unlock massive system elasticity.

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#1 about 6 min

Core principles and promises of the Reactive Manifesto

The Reactive Manifesto defines essential software requirements for responsiveness, elasticity, and resilience under heavy computational load.

#2 about 3 min

Comparing blocking requests with message-driven execution flows

Fire-and-forget messaging frees execution threads compared to traditional remote procedure calls within a blocking architecture.

#3 about 4 min

Exploring concurrency concepts through task distribution analogies

Dividing massive workloads into small, independently processed pieces prevents system bottlenecks and improves overall elasticity.

#4 about 3 min

Framework adoption challenges in the reactive programming ecosystem

Steep learning curves and debugging complexities often hinder the widespread adoption of tools like spring webflux and rxjava.

#5 about 4 min

Implementing non-reactive Java API data processing pipelines

A traditional imperative Java approach utilizes spring resttemplate to sequentially fetch, filter, and save external API data.

#6 about 4 min

Refactoring data processing pipelines using Spring WebFlux streams

Asynchronous reactive streams use flux collections and flatmap operations to handle data processing logic without blocking resources.

#7 about 4 min

Managing debugging and execution order in reactive streams

Asynchronous event processing fundamentally alters how IDE breakpoints trigger and changes the sequential order of application logs.

#8 about 2 min

Evaluating Project Loom and legacy non-reactive system integrations

Lightweight virtual threads and legacy database drivers present ongoing integration considerations and architectural alternatives for reactive paradigms.

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