Teradata Unveils QueryGrid 

Teradata today delivered Teradata QueryGrid, the only software that optimizes analytics across the enterprise and beyond.

Organizations are seeking the ability to scale the breadth and sophistication of their data analytics to respond to the demands of business operations. The challenge is how to best orchestrate a wide variety of new analytic engines, file systems, storage techniques, procedural languages and data types into one cohesive, interconnected, and complementary analytic architecture.

"Attempts at federation have been unsuccessful for many reasons. To deliver value from big data, customers should create an architecture that allows the orchestration of analytic processes across parallel databases rather than federated servers. Teradata QueryGrid is the most flexible solution with innovative software that gets the job done," said Scott Gnau, president, Teradata Labs. "After the user selects an analytic engine and a file system, Teradata software seamlessly orchestrates analytic processing across systems with a single SQL query, without moving the data. In addition, Teradata allows for multiple file systems and engines in the same workload."

"Teradata pioneered integration with Hadoop and HCatalog with Aster SQL-H to empower customers to run advanced analytics directly on vast amounts of data stored in Hadoop," said Ari Zilka, CTO, Hortonworks. "Now they are taking it to the next level with pushdown processing into Hadoop, leveraging the Hive performance improvements from Hortonworks’ Stinger initiative, delivering results at unprecedented speed and scale."

Teradata QueryGrid changes the rules of the game by giving users seamless, self-service access to data and analytic processing across different systems from within a single Teradata Database or Aster Database query. Teradata QueryGrid uses analytic engines and file systems to concentrate their power on accessing and analyzing data without special tools or IT intervention. It minimizes data movement and duplication by processing data where it resides.