Abstract
Big data analysis has influenced the industry market. It has a significant impact on large and varied datasets to exhibit the hidden patterns and other revelations. Apache Hadoop, Apache Flink and Apache Storm are some commonly used frameworks for big data analysis. Apache Spark is a consolidated big data analytics engine and provides absolute data parallelism. This paper scrutinizes a technical review on big data analytics using Apache Spark and how it uses in-memory computation that makes it remarkably faster as compared to other corresponding frameworks. Moreover, Spark also provides exceptional batch processing and stream processing capabilities. Furthermore, it also discuses over the multithreading and con-currency capabilities of Apache Spark. The point of convergence is architecture, hardware requirements, ecosystem, use cases, features of Apache Spark and the use of Spark in emerging technologies.