A distributed file system, a MapReduce programming framework, and an extended family of tools for processing huge data sets on large clusters of commodity hardware, Hadoop has been synonymous with "big data" for more than a decade. But no technology can hold the spotlight forever. While Hadoop remains an essential part of the big data platforms, and the major Hadoop vendors--namely Cloudera, Hortonworks, and MapR--have changed their platforms dramatically. Once-peripheral projects like Apache Spark and Apache Kafka have become the new stars, and the focus has turned to other ways to drill into data and extract insight. Let's take a brief tour of the three leading big data platforms, what each adds to the mix of Hadoop technologies to set it apart, and how they are evolving to embrace a new era of containers, Kubernetes, machine learning, and deep learning.