There was a time, a little over two years ago, when SQL-on-Hadoop was about cracking open access to Hadoop data for those with SQL skillsets and eliminating the exclusivity of access that Hadoop/MapReduce specialists had on the data. Yes, some architectural details – like whether the SQL engine was hitting the data nodes in the Hadoop cluster directly – were important too. But, for the most part, solutions in the space were neatly summed up by the name: SQL, on Hadoop.
Today, SQL-on-Hadoop solutions are best judged not by their SQL engines per se, but instead by the collaborative scenarios they enable between Hadoop and the conventional data warehouse.