Apache Spark is an open-source, distributed processing system used for big data workloads. It uses in-memory caching and optimised query execution for fast queries in big data. In other words: Apache Spark is a very fast engine for large-scale data processing. 

Apache Spark is fast and widely applicable

Because Apache Spark runs on main memory (RAM), not only is the system very fast, it also has multiple applications, such as executing distributed SQL, creating data pipelines, entering data into a database, executing Machine Learning algorithms, and working with graphs and data streams. 

Apache Spark can distribute tasks across multiple computers, which is relevant when you work with big data and machine learning, which require a lot of computing power. Moreover, thanks to the user-friendly API, the programming burden is relatively small. 

Want to learn more about Apache Spark?

Learn more practical information about Apache Spark here, including Azure HDInsight. The HSO Analytics team has a wealth of knowledge and experience in implementing big data, IoT and Advanced Analytics (AI) solutions.