For all the hype surrounding the #NoSQL movement, SQL remains the lingua franca for queries across both relational and other types of emerging databases. In fact, one of the fastest growing use cases for SQL is on top of #Hadoop clusters. This week, #Hortonworks underscored that point at a Dataworks Summit/Hadoop Summit Munich conference via a release to the Hortonworks Data Platform (HDP) that adds support for an instance of Apache Hive 2.0 with Live Long and Process (LLP) capabilities that runs in memory. Rather than having to invest in a commercial relational database, Hortonworks CTO Scott Gnau says HDP 2.6 provides all the advantages of SQL running on a platform that can handle several orders of magnitude more data. Because Hive 2.0 LLP runs in memory, any query against that data can now be processed in the sub-second range, says Gnau. Armed with these capabilities, Gnau says, many IT organizations will increasingly be migrating analytics applications off relational databases in favor of directly accessing data stored in Hadoop.
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