Tag: SQL on Hadoop

On June 9, JethroData announced the finalization of an $8.1M Series B funding raise led by Square Peg Capital with additional participation from Pitango Venture Capital. The funding will be used to accelerate product development and sales and marketing initiatives for the company’s breakthrough SQL on Hadoop offering. As told to Cloud Computing Today in a phone interview with JethroData CEO Eli Singer, the company’s SQL on Hadoop platform differentiates itself from the landscape of SQL interfaces for Hadoop by way of its superior performance with respect to querying Hadoop-based data. The JethroData platform derives its exceptional performance by indexing Hadoop data and subsequently limiting queries only to rows of data containing the relevant indices. Rather than querying the entire cluster, JethroData’s queries hone in on the subset of Hadoop data containing the relevant index attributes and thereby delivers results in a fraction of the time required by its competitors. For the use case of constructing predictive modeling algorithms, however, JethroData queries the entire Hadoop dataset in question as opposed to a subset for the purpose of creating models that illustrate trends and variations in data points and various aggregations. The platform’s design supports interactive business intelligence applications that depend on rapid data refreshes for both their analytics and visualizations and, as such, integrates with the likes of Tableau, MicroStrategy and Qlik. Tuesday’s announcement of the company’s funding raise validates the company’s early traction and supports JethroData’s claim to deliver queries on the order of 100x faster than competing SQL on Hadoop platforms.