Which Big Data technology is known for handling real-time analytics?

Apache Spark is known for its ability to handle real-time analytics due to its in-memory processing capabilities and support for a wide variety of workloads, including streaming data. Unlike traditional batch processing frameworks, Spark is designed to process data in real time, allowing organizations to analyze information as it is generated. This capability makes it particularly valuable for use cases that require immediate insights, such as fraud detection, monitoring user behavior, and real-time data processing.

In addition to real-time analytics, Spark supports complex computations and can manage various data processing tasks beyond just analytics, which adds to its versatility. The combination of fast execution and the ability to easily perform iterative algorithms makes Spark well-suited for both real-time and large-scale data processing scenarios.