The document discusses several big data frameworks: Spark, Presto, Cloudera Impala, and Apache Hadoop. Spark aims to make data analytics faster by loading data into memory for iterative querying. Presto extends R with distributed parallelism for scalable machine learning and graph algorithms. Hadoop uses MapReduce to distribute computations across large hardware clusters and handles failures automatically. While useful for batch processing, Hadoop has disadvantages for small files and online transactions.