(NASDAQ: SPLK), provider of the leading software platform for real-time Operational Intelligence, today announced version 6.1 of Hunk™: Splunk® Analytics for Hadoop and NoSQL Data Stores. Hunk 6.1 makes it even faster and easier to turn raw, unstructured data in Hadoop and NoSQL data stores into business insights. Accelerated reports in Hunk significantly improve reporting times, while interactive dashboards deliver rich self-service analytics without fixed schemas or the need to move data. Hunk 6.1 extends the power of Hunk beyond Hadoop through streaming resource libraries for NoSQL and other data stores such as Apache Accumulo, Apache Cassandra, MongoDB and Neo4j.
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“Hunk brings simplicity to the complex world of analyzing massive volumes of data stored in Hadoop and NoSQL,” said Sanjay Mehta, vice president of product marketing, Splunk. “Hunk is ideal for organizations seeking a faster, easier way to unlock the value from huge amounts of historical data at rest. Alternate approaches require specialized skillsets, fixed schemas, complex programming or moving the data – all of which add up to wasted time and lost opportunity. We are excited to see what NoSQL developers can do now that we have extended Hunk’s capability from Hadoop to NoSQL data stores.”
“While adoption of Hadoop and other Big Data stores continues to grow, our research indicates that the analytics outcomes from these projects are limited. With a focus on faster analytics and quick time to value, Hunk aims to change this,” said Tony Cosentino, vice president and research director, Ventana Research. “By now enabling analytics capabilities to NoSQL developers, in addition to Hadoop developers, Splunk opens up additional opportunities for Big Data analytics.”
Full-featured Analytics Platform for Hadoop and NoSQL
Hunk 6.1 contains significant new and updated product features to help organizations unlock the business value of data in Hadoop and NoSQL data stores:
- Splunk Virtual Index: Patent-pending technology that decouples the storage tier from the data access and analytics tiers enabling Hunk to route requests to different data stores.
- Report Acceleration: Transparently cache search results in Hadoop, improving reporting response times and performance without moving data. Drives more efficient utilization of Hadoop resources – as the amount of data grows and the number of queries increases.
- Interactive Dashboards and Charts: Rapidly build custom dashboards with a new dashboard editor and deliver an enhanced analytics experience with charting overlay, pan-and-zoom controls and in-dashboard drill downs.
- Embedded Analytics: Embeds Hunk charts and dashboards into common third-party business applications.
- Streaming Resource Libraries – Enables developers to stream data from NoSQL and other data stores, such as Apache Accumulo, Apache Cassandra, MongoDB and Neo4j, for exploration, analysis and visualization in Hunk.
- Support for Multiple File Formats: Automates access to text files, sequence files, Record Columnar Files (RCFile), Optimized Row Columnar (ORC) files and Parquet columnar files.
- Pass-through Authentication: Enables submission of MapReduce jobs and secure access to Hadoop clusters using the authenticated credentials and roles assigned by IT.