RxJava 4 is a reactive programming library for the JVM, implementing the Reactive Streams specification via `java.util.concurrent.Flow` (Publisher/Subscriber). It provides six core reactive types: `Flowable` (backpressured), `Observable` (unbounded), `Single` (single value), `Maybe` (optional value), `Completable` (completion signal), and the new `Streamable` (pull-based streaming with `CompletionStage`). The library offers a comprehensive set of operators (map, filter, flatMap, concat, merge, window, buffer, etc.) for composing asynchronous data flows, along with schedulers for threading control (`Schedulers.computation()`, `Schedulers.io()`, `Schedulers.virtual()` for virtual threads). It includes advanced features like operator fusion (`QueueFuseable`), backpressure strategies, and configurable operator parameters via immutable records. The architecture is modular: each operator is a final class extending the base reactive type with an inner observer/subscriber class managing state. External dependencies are minimal (only JDK standard library), and the library is designed for embedding in applications, frameworks, and Android. Key entry points are the static factory methods on `Flowable`, `Observable`, `Single`, `Maybe`, `Completable`, and `Streamable`. Data flows are constructed by chaining operators that transform and combine reactive streams, with lifecycle managed through `Disposable` and `Subscription` contracts.

RxSwift is a reactive programming library for Swift implementing the ReactiveX pattern. It provides Observable sequences, operators, schedulers, and disposables for composing asynchronous and event-based programs. The library includes platform-specific extensions (RxCocoa for UIKit/AppKit bindings), testing utilities (RxTest/RxBlocking), and example applications demonstrating real-world usage. Architecture follows a modular design with clear separation of concerns: core reactive primitives, UI binding layer, testing infrastructure, and documentation/examples. Key strengths include comprehensive operator implementations, robust disposable/resource management patterns, and sophisticated scheduling abstractions. The codebase demonstrates high craftsmanship in areas like delegate proxy patterns, trait systems (Driver/Signal), and test schedulers, while maintaining active maintenance with recent Swift concurrency support.