What does the term "scalability" mean in Big Data systems?

In the context of Big Data systems, "scalability" refers to the capacity of the system to effectively manage and process an increasing amount of data and user demand without deteriorating in performance. This means that as the volume of data grows, either by adding more data sources or accommodating more users, the system can adapt by enhancing its resources—such as adding more servers, memory, or storage—while maintaining consistent levels of performance and response times.

Scalability is critical for Big Data systems because these systems often need to grow alongside the ever-expanding datasets generated from various sources. A scalable system ensures that businesses can continue to make data-driven decisions even as their data needs evolve. This characteristic is essential for maintaining operational efficiency, user satisfaction, and accurate insights, making it a fundamental quality in designing and evaluating Big Data architectures.