Jethro, provider of an index-based SQL enterprise platform, is launching Jethro 3.0, combining the power of indexing architecture with “auto-cubes” to accelerate all possible business intelligence use cases using big data.
With Jethro 3.0, costly, labor intensive tasks such as manually building summary tables, conducting maintenance work with incremental updates, or performing data re-engineering for new applications, are all automated within the platform.
"Today’s approach to BI on Big Data is not working. Under the SQL-on-Hadoop hype lies monumental failure rates with existing approaches,” said Eli Singer, CEO of Jethro. “With a purposely built tool like Jethro, which leverages a combined automation and acceleration architecture, 3.0 provides high-performing enterprise BI at lower Big Data costs. Nobody else makes existing BI applications work on big data like Jethro.”
With the advancement of aggregated auto-cubes, Jethro 3.0 boosts improved enterprise security features including Lightweight Directory Access Protocol (LDAP) authentication and role-based permissions, allowing customers to set clearly-defined security responsibilities within their own company.
Additionally, Jethro 3.0 offers the ability to directly load data from Hadoop tables and an improved management graphical user interface (GUI).
For more information about this update, visit www.jethrodata.com.