As data volumes exponentially increase, traditional data processing methods become inadequate. Ultra-large Java arrays present performance risks and memory constraints, necessitating alternative strategies like streaming, chunk processing, caching, and distributed frameworks such as Hadoop and Spark. Adapting to these approaches enhances efficiency and scalability in managing Big Data.