You've built a data lake, so now what? Hunk is the big data analytics platform that lets you rapidly explore, analyze and visualize data in Hadoop. It provides a simple, integrated experience designed to provide insights from your big data without specialized skills, fixed schemas or months of development.
A Petabyte of Data Is a Terrible Thing to Waste
Hunk gives you the power to rapidly detect patterns and find anomalies across petabytes of raw data in Hadoop without the need to move or replicate data.
- Drive down costs by easily rolling historical data from Splunk Enterprise to HDFS and Amazon S3
- Interactively query raw data by previewing results and refining searches using the same Splunk Enterprise interface
- Quickly create and share charts, graphs and dashboards
- Ensure security with role-based access control and HDFS pass-through authentication
- Hunk natively supports Apache Hadoop and Amazon EMR, Cloudera CDH, Hortonworks Data Platform, IBM InfoSphere BigInsights, MapR M-series and Pivotal HD distributions
Hunk Product Tour
Analyze Raw Data
Edit Dashboards and Views
Rich Development Environment
Splunk Virtual Index Technology
Hunk's schema on-the-fly delivers the flexibility to run queries on your Hadoop data without the need to know up front what questions or reports you will need to ask later. Hunk works on Apache Hadoop and most major distributions, including those from Cloudera, Hortonworks, IBM, MapR and Pivotal, and supports both first-generation MapReduce and YARN.
When you run a query in Hunk, it streams back interim results immediately while the MapReduce job continues to run in the background. This delivers a faster, more interactive experience because you can pause and refine queries without having to wait for full MapReduce jobs to finish.
Hunk empowers business and IT teams to analyze raw data in Hadoop. Data models describe relationships in the underlying raw data, making it more meaningful and usable. Quickly generate charts, visualizations and dashboards using the pivot interface. Transparently cache search results in Hadoop to improve reporting response times and performance without the need to move your data.
An easy-to-use dashboard editor enables you to create and edit dashboards that integrate multiple charts and views to satisfy the needs of multiple business and IT stakeholders. Role-based access controls protect your sensitive data. Additional features such as charting overlay, pan-and-zoom controls and in-dashboard drill downs deliver a powerful analytics experience. You can even embed charts and dashboards into existing third-party business applications.
The Splunk Virtual Index is a patent-pending capability that decouples the Splunk storage tier from the data access and analytics tiers, enabling Hunk to transparently route requests to different data stores. Hunk incorporates Splunk data models, pivot, dashboarding, role-based access controls and the Splunk developer environment. The analytics tier is powered by Splunk’s Search Processing Language (SPL™), the industry-leading method for interactive data exploration across large, diverse data sets.
What's New in Hunk 6.4?
Hunk 6.4 makes it faster and easier to unlock the business value of big data in Hadoop.
Advanced Analytics and VisualizationsUncover rare events using anomaly detection, quickly spot variances across customizable geographic areas, and get context from big data with flexible formatting with visual cues.
Open Access to Archived DataProvide broader access to Hunk data for data scientists and analysts who use third-party Hadoop tools such as Hive or Pig.
Integration with Amazon EMRLeverage automatically configured Hunk instances provisioned by AWS, priced hourly, for data in Amazon EMR and S3, directly from the Amazon EMR console.
"Hunk has been an essential point-of-entry to the Hadoop space. It allows for fast, interactive exploration and validation of our data."
-Michael Saia, Infrastructure Team Lead
"The marriage of Hunk and MongoDB enables our joint customers to understand and analyze their data faster than ever."