Initially released in beta at the Hadoop Summit North America 2013 conference in San Jose, Calif., in June, Hunk is a full-featured, integrated analytics platform for Hadoop that enables users to interactively explore, analyze and visualize historical data in Hadoop.
Essentially, Hunk is a software product from Splunk that integrates exploration, analysis and visualization of data in Hadoop. It enables users to interact with and analyze data in Hadoop without programming, integrations or forced data migrations, the company said.
Indeed, Splunk officials said Hunk is built on patent-pending virtual index technology that delivers self-serve analytics without the need for specialized programming skill sets, fixed schemas or costly integrations.
"With Hunk, it's not about re-tooling or learning new things; it's about using the Web skills you have," said Jon Rooney, director of developer marketing at Splunk. "It's really about enabling developers where they are," he added.
“Hunk is transforming the way organizations analyze their data in Hadoop by replacing drawn out development cycles with software that enables customers to deploy and deliver insights in hours instead of weeks or months,” said Sanjay Mehta, vice president of product marketing at Splunk, in a statement.
Hunk is available for download for a free 60-day trial with no caps on data size or number of Hadoop nodes.
“Hadoop is an increasingly important technology and many organizations are storing vast amounts of data in Hadoop," Mehta said. "However, this often creates a problem because the data sets become too big to move and more traditional approaches to analytics of raw data in Hadoop require brittle, fixed schemas. These are key reasons our customers consistently tell us about the cost, time and sheer difficulty of getting analytics out of their Hadoop clusters. With Hunk, we applied everything Splunk has learned from 10 years of experience with more than 6,000 customers to this unique challenge.”
“Splunk was early in understanding the importance of machine-generated data, and in building an analytic stack focused on it, with strengths in quasi-real-time interfaces and in schema-on-need handling of time series data,” said Curt Monash, president of Monash Research and editor of DBMS 2, in a statement. “Now Splunk’s analytic tools are also available for machine-generated data stored in Hadoop. Splunk has further strengthened its schema-on-need story by adding its new higher-performance data store.”