Splunk, a big data aggregation and intelligence tool, is launching in a special edition for Hadoop. Appropriately named Splunk Enterprise with Hadoop, the solution integrates the analytics engine into Splunk in order to provider a number of key advantages to users that leverage both technologies.

“This integrated offering provides access to Splunk’s real-time capabilities, ease-of-use and enterprise functionality that people in IT around the world have come to love,” said Erik Swan, co-founder and chief technology officer at Splunk.

Data collected by Splunk Enterprise can be indexed and analyzed, at which point the dataset can be ported over to Hadoop for archival or batch analysis. In addition MapReduce queries can be run from Splunk against data stored in a company’s Hadoop deployment, in order to process it into dashboards or carry out addition analysis.

Along with these core features, the integrated solution also extends Splunk’s authentication and role-based access capabilities to Hadoop, and a number of SDKs and APIs enable developers to stream the data between the applications, as well as third party ones.

Todd Papaioannou, entrepreneur in residence at Battery Ventures called the integration of Hadoop and Splunk “a very natural fit,” citing the two tools’ complementing functionality. The deep integration (which can further be extended in-house for specific purposes) adds to that.

One of the companies using Splunk and its machine data management tool is Etsy, an online marketplace of various crafted goods. Etsy is looking in the direction of big data as one means of expansion – in particular a recommendation feature designed to haul in new users.  Visitors are welcomed with a line-up of images covering various categories of the products available on the site, through which they can receive suggestions about items they may be interested and view others’ picks.