Which component of Spark is specifically tailored for handling graph data?

GraphX is the component of Apache Spark that is specifically designed to handle graph data. It provides an API for manipulating graphs and performing graph-parallel computations while leveraging the strengths of Apache Spark's scalable, distributed architecture.

GraphX allows users to create, transform, and query graphs with ease, making it suitable for tasks such as social network analysis, fraud detection, and any application where relationship and connection data are critical. It offers a range of built-in graph algorithms, supporting advanced analytical capabilities on graph structures.

In contrast, the other components serve different purposes: Streaming is focused on processing real-time data streams, MLlib serves as the machine learning library for Spark, and Spark SQL is used for working with structured data, allowing for querying data using SQL-like syntax. None of these components specialize in graph data or provide the same level of functionality for graph processing as GraphX does.