SQL for Big data – we are excited.

Posted on 28 Aug 2013 in   Big Data



Traditional data warehouses based on relational database technologies have been around for a long time and have mature sets of tools for querying and analysis. Business users use SQL as the query language to perform ad-hoc queries against these warehouses. Also, reporting tools like Cognos, Business Objects, MicroStrategy rely on SQL heavily. The real value of Hadoop is realized when users can access and perform ad-hoc queries data directly on Hadoop using tools that support SQL.

Based on this post , we are betting that the adoption of SecondPrism’s YADA platform is going to easier with Hadoop.

Some of the key things to note are the technology leaders who are backing this up are : Hortonworks, Facebook, Microsoft and SAP among others. One of the key features these folks are working on is an Improved SQL Interface. For example Hortonworks With Stinger, Hive is more suitable to deliver the decision support queries people want to perform in Hadoop. This includes adding analytics features like the OVER clause, support for subqueries in WHERE, and aligning Hive’s type system more with the standard SQL model.