Reactive programming with RxJava enables handling asynchronous data streams and events. Observable emits data; Observer receives and processes it. Operators transform, filter, and combine data streams. map transforms each emitted item. flatMap transforms emissions into new Observables and flattens them. filter passes only items matching a predicate. zip combines emissions from multiple Observables. debounce handles rapid input events like search typing. Schedulers control threading: subscribeOn for subscription, observeOn for observation. AndroidSchedulers.mainThread provides UI thread execution. CompositeDisposable manages subscription lifecycle. RxBinding library bridges UI events to Observables. Retrofit integrates natively with RxJava for network calls. Room supports reactive queries returning Observable or Flowable. Error handling uses onErrorResumeNext and retry operators. Backpressure strategies handle fast producers with slow consumers. Testing uses TestObserver and TestScheduler. RxJava's learning curve is steep but powerful. Kotlin Coroutines are increasingly preferred over RxJava for new projects. Understanding reactive patterns remains valuable regardless of implementation technology.