Reactive Streams in Java

Reactive Streams is an initiative to offer a standard for asynchronous stream processing with non-blocking backpressure. It encompasses efforts aimed at runtime environments JVM and JavaScript as well as network protocols.

In the Java community, “Reactive Streams” is a widely heard term. Reactive Programming has started gaining popularity these days, and in most of the Java seminars, it has become a substantial topic of discussion. The Functional Programming paradigm excitingly complements the Reactive Programming paradigm. It is way different than the traditional functional programming in Java. Just like Object Oriented programming, Reactive Programming has a different standard.

The Problem:

The Scope:

The Reactive Streams API is the result of a partnership between the developers from Kaazing, Red Hat, Netflix, Pivotal, Twitter, Typesafe, and many others. Reactive Streams are much like JPA or JDBC. Both of these are API specifications. From the JDBC specification, you can obtain the Java Data source.

Oracle JDBC implementation provides an implementation of the Datasource interface. Like JDBC or JPA, Reactive Streams offers an API interface we can code without having to worry about the underlying implementation.

Reactive Programming:- There is a massive hype about Reactive Programming in the market. The most important aspect to understand Reactive Programming is to understand the Reactive Manifesto. The Reactive Manifesto is an instruction to build modern, cloud-scale architectures.

Reactive Manifesto:-

1.Responsive: The system responds promptly. Responsiveness of a Program means, the problems can be identified very quickly and dealt with efficiently.

2.Resilient: The system stays responsive at the advent of a failure situation. It applies to the mission-critical circumstances. It achieves resilience via replication, isolation, delegation, and containment. Failures are present within each component; this isolates the elements from each other and thereby ensures that parts of the system falter and recover without compromising the whole system. It is a more fail-safe scenario, and the entire system doesn’t get jeopardized.

3.Elastic: The system stays responsive under differential workloads.

4.Message Driven: Reactive Systems are based on asynchronous message-passing to establish a boundary between components that comes with location transparency, isolation, and loose coupling. This boundary helps the system delegate failures as messages.

The first three aspects are more related to Software Architecture choice. It’s obvious to see why technologies such as microservices, Docker, and Kubernetes are essential facets of Reactive systems. Executing a LAMP stack on a single server does not fulfill the objectives of the Reactive Manifesto.

The Reactive Streams API has four interfaces:

Reactive Streams Implementation for Java-

The reactive landscape in Java keeps evolving, maturing, and advancing while becoming popular with time.

RxJava: RxJava refers to the Java implementation out of the ReactiveX project. While writing, the ReactiveX project had applications for Java, Clojure, JavaScript, .NET (C#), Scala, C++, Ruby, Python, PHP, Swift, and several others.

ReactiveX offers a reactive twist on the GoF Observer pattern. ReactiveX calls their approach ‘Observer Pattern Done Right.’ RxJava predates the Reactive Streams specification. Even though RxJava 2.0+ implements the Reactive Streams API specification, you can observe a marginal implementational difference.

Akka Streams: Akka Streams entirely implements the Reactive Streams specification. Akka helps Actors to deal with the streaming data. While Akka Streams is compliant with the Reactive Streams API specification, the Akka Streams API is decoupled from the Reactive Streams interfaces. Akka Streams is a third-generation Reactive library.

Ratpack: Ratpack is a collection of Java libraries for building high-performance HTTP based interactive applications of today. Ratpack uses Java 8, Netty, and Reactive principles.

Vert.x: Vert.x is an Eclipse Foundation project. It is a multilingual event-driven application framework for the JVM. Reactive support in Vert.x is similar to Ratpack. Vert.x allows using RxJava or their native implementation of the Reactive Streams API.

Conclusion

In Java 9, Reactive Streams is officially part of the Java API. Before Reactive Streams, the various reactive libraries had no means of interoperability. They could not communicate with each other. Early versions of RxJava was not compatible with old versions of project Reactor.

Interoperability is an essential aspect of Reactive Programming now. For example, MongoDB has implemented a Reactive Streams driver. Now, in highly user-driven and interactive applications, we can use a Reactor or RxJava to consume data from a MongoDB.

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