KNIME is the leading open platform for data-driven innovation helping organizations to stay ahead of change. Use the open-source, enterprise-grade analytics platform to discover the potential hidden in your data, mine for fresh insights or predict new futures.
KNIME Big Data Extension
With the KNIME Big Data Extension access to your data is now even easier. As part of KNIME.com AG’s commercial offerings, the extension offers a set of nodes for accessing Hadoop/HDFS via Hive from inside KNIME. It brings with it all required libraries – after installing the extension from the KNIME Update Site no additional steps are required. Please have a look at the KNIME Big Data Extension  product sheet for details.
A Few More Details
KNIME , pronounced [naim], is a modern data analytics platform that allows you to perform sophisticated statistics and data mining on your data to analyze trends and predict potential results. Its visual workbench combines data access, data transformation, initial investigation, powerful predictive analytics and visualization. KNIME also provides the ability to develop reports based on your information or automate the application of new insight back into production systems. KNIME Analytics Platform is open source and available under GPL license . It can be extended with KNIME Commercial Software to include professional support, productivity and collaboration functionality, providing the best of both worlds. Take a look at the open source KNIME Analytics Platform, or better yet simply download  it and use it for free!
Dependency Compatibility Information: MapR4.1|Hive|JDBC Application Version: Application Version: 1.0
The Big Data Extension can be installed via the
KNIME Update Manager.
Go to File → Install KNIME Extensions... and select the appropriate extension from the KNIME.com Extension Store category. For further details go to https://tech.knime.org/installation-instructions
KNIME Analytics Platform now provides easy access to a
collection of example workflows  using the KNIME Explorer view. This is
the same place where you see your local workflows.
For big data examples go to the 017_BigData directory.