They use distributed computing architectures to process large-scale data across multiple real-time analytics platforms nodes. Data is partitioned and processed in parallel, allowing high throughput and low latency. Technologies like Kafka handle data ingestion, while stream processors manage computation. This architecture ensures scalability even when dealing with millions of events per second.