Apache Spark is a unified distributed computing engine across different workloads and platforms. Spark can connect to different platforms and process different data workloads using a variety of paradigms such as Spark Streaming, Spark ML, Spark SQL, and Spark Graphx.
Apache Spark is a fast in-memory data processing engine with elegant and expressive development APIs, which allow data workers to efficiently execute streaming machine learning or SQL workloads that require fast interactive access to data sets.
Additional libraries built on top of the core allow the workloads for streaming, SQL, graph processing, and machine learning. SparkML, for instance, is designed for data science and its abstraction makes data science easier.
Spark provides real-time streaming, queries, machine learning, and graph processing. Before Apache Spark, we had to use different technologies for different types of workloads. One for batch analytics, one for interactive queries, one for real-time streaming...