Which Azure service is specifically known for its applications in big data and real-time analytics?

Azure Stream Analytics is specifically designed for big data and real-time analytics. It provides the ability to process and analyze data streams from various sources in real-time, making it an ideal choice for scenarios where timely insights are crucial. Stream Analytics allows for the ingestion of large volumes of data, often coming from IoT devices, applications, or any event-driven systems, and then applies real-time analytics to generate quick insights. Its capabilities include querying streaming data with a SQL-like syntax, which simplifies the integration with other Azure services.

In contrast, while Azure Data Factory is a powerful data integration service designed for data movement and orchestration, it focuses more on batch processing and ETL (extract, transform, load) workflows rather than real-time analytics. Azure SQL Database is a relational database service that supports many applications but is not specifically tailored for real-time analytics on big data streams. Azure Databricks provides a collaborative platform for big data analytics and machine learning, optimizing processing of large datasets, but it does not specialize in real-time analytics in the same streamlined manner as Stream Analytics does.