Scalability in big data refers to the ability of an application or system to handle increasingly larger amounts of data without compromising its performance. It is a critical factor in big data processing because as the volume and variety of data grow, traditional systems and tools may struggle to keep up. The scalability of a big data system is typically achieved through distributed computing and parallel processing, allowing the workload to be spread across multiple machines or nodes. This approach enables the system to handle massive data volumes and provides faster access and processing, ensuring optimal performance even under heavy loads.
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