Splunk has long be known for working with machine data, of which the most prevalent is time-series text log data. Last year however, Splunk released Hunk to allow for analytics of Hadoop data stored in HDFS utilizing MapReduce. Offering the full power of Splunk’s analytics, search language, dashboarding & visualizations, role based access controls, and offering a seamless experience of querying the data in a Splunk index or a virtual index in Hadoop, Hunk provides powerful new capabilities to Splunk’s userbase. In Hunk 6.1 recently released, Hunk has expanded the virtual index functionality further by opening this technology to any data store via the same API the Hadoop integration uses to Hunk. Splunk and MongoDB have partnered to offer a results provider for MongoDB, allowing users of Hunk to query data in MongoDB the same way they would query data in a Splunk index or Hadoop virtual index. Come learn how Splunk and MongoDB have built this integration and how you can put it to use to query large scale data sets in MongoDB and visualize and analyze them utilizing Hunk!