The growth of big data has driven the need for efficient data processing methods, especially in cloud computing environments. This study evaluates distributed computing frameworks like Apache Hadoop and Apache Spark for optimizing big data processing. By analyzing different configurations, we demonstrate how distributed systems can significantly reduce processing time and improve resource utilization, making them ideal for handling complex datasets in cloud environments.