One of Spark's key features is its ability to perform in-memory processing, which significantly speeds up computations when compared to traditional disk-based systems. It also offers built-in libraries for machine learning (MLlib), graph processing (GraphX), and streaming (Spark Streaming), making it a versatile tool for data analysis and processing.

Apache Spark is an open-source distributed computing system designed for big data processing and analytics. It provides a unified analytics engine that supports batch processing, real-time streaming, machine learning, and graph processing.

Spark is built around a resilient distributed dataset (RDD) abstraction, which allows developers to perform in-memory processing in a fault-tolerant manner. It provides high-level APIs in Java, Scala, Python, and R, making it easy to develop applications with complex data processing requirements.