r2dbc-postgresql VS reactor-core

Now that we have an application, let's turn it into a reactive application. For this, we will replace Spring Web dependency with Spring WebFlux, Spring Data JPA with Spring Data R2DBC. We will also add R2DBC dependency for our H2 database. R2DBC works with a reactive driver so it will integrate nicely with the rest of our application to allow us database access in a non-blocking way.

However, if you really expect a lot of users (especially concurrent ones) to use your API, you should delve into the world of reactive programming. Use tools like RxJS (JS/TS) or Project Reactor (Java) in such a case, preferably in combination with a broker like Kafka or RabbitMQ. R2DBC is also great for a data store. Then of course if you want to go one step further, there also exists the less popular but very interesting Actor model which Akka easily has ported into Java.

I was exploring reactive streams with project reactor and I encountered a use case where I needed to skip to the next event if an error occurred during the processing of the current event (e.g. deserialization issue).

Kotlin also has a construct for asynchronous collections/streams. Kotlin's version of AsyncSequence is called a Flow. Just as Swift's AsyncSequence builds upon prior experience with RxSwift and Combine, Kotlin's Flow APIs build upon earlier stream/collection APIs in the JVM ecosystem: Java's RxJava, Java8 Streams, Project Reactor, and Scala's Akka.

Java's projectreactor.io ? It is widely used in Java world, see Spring WebFlux.

I guess more a closer comparison would be with the Project Reactor https://projectreactor.io/ which is also a low level framework for data processing.

Spring Framework is one of the most popular choices for web applications. It comes with a great ecosystem, tooling, and support. Spring applications are mainly written in Java. While they can serve quite well in many different domains and use cases, they may not be a good fit for modern-day applications which require low-latency and high-throughput. This is where the reactive programming paradigm could help because the paradigm is designed to address these issues by its non-blocking nature. Spring already supports reactive programming via Project Reactor.

The reactive streams API provides the specification for non-blocking async streams processing with back pressure mechanism, and Project Reactor is an implementation written in java.

https://projectreactor.io/ https://docs.oracle.com/javase/8/docs/api/java/util/stream/Stream.html https://rxjs.dev/ https://developer.android.com/kotlin/coroutines https://developer.apple.com/documentation/combine

With respect to Loom, it could be much easier for synchronous and reactive code to interoperate using schedulers that take advantage of Loom. The impact of Loom on Project Reactor was discussed in #3084, you might find it interesting.