Providing more access to more data for more users is the holy grail of modern analytics. To help organizations answer questions with data spread across disparate analytics systems and data repositories, Teradata has expanded its QueryGrid technologies.
The expanded choices span Teradata-to-Cloudera, Aster-to-Cloudera, Teradata-to-Aster, and Teradata-to-Teradata to orchestrate the processing of data across an analytical ecosystem.
In addition, Teradata has enhanced the existing Teradata-to-Hortonworks Data Platform integratio; and MapR and Teradata have provided more information about their previously announced Teradata-MapR integration.
Specific integrations included in the announcement cover Teradata 14.10 to Cloudera CDH 4.3, CDH 5.1, Hortonworks 2.1, as well as MapR 3.1.1. In addition, Teradata has announced a connector for Teradata 15.00 to Hortonworks 2.1, plus Kerberos and LDAP support; and Aster 6.00 to Cloudera CDH 4.3, and CDH 5.1. A Teradata 15.00 to Teradata 15.00 connector; and a Teradata 15.00 to Aster 6.10 has also been announced.
“With this announcement we have our foot on the gas pedal,” Imad Birouty, director of product marketing, Teradata. “We have seven updates. We are announcing new connectors that are on their way, announcing that we have delivered on the connectors that we previously announced, and we are refreshing previously-released connector versions of the technologies.”
Teradata QueryGrid offers customers seamless self-service access to data and analytic processing across different systems without special tools or IT intervention, a capability that has become increasingly important as open source technologies become a major component of best-of- breed enterprise analytic environments.
“With QueryGrid we are enabling customers to use either their Teradata Database or their Aster Data Database to run analytics there and to reach out to other sources, such as Hadoop, MongoDB, or an Oracle Database so the data warehouse becomes a gateway to running analytics against other systems so they are not bound by just the technology of their data warehouse,” said Birouty.
“When Teradata reaches out to Hadoop we are really enabling a different class of workload. Customers are going to have massive amounts of data sitting in Hadoop - things like sensor data and web click data. But users may not be MapReduce experts so with QueryGrid, we give them the ability to grab that data, massage it run their queries and return the results,” said Birouty.
And, with the Teradata to Teradata connectors, greater architectural flexibility is enabled. “We have a Teradata platform family, each platform has different capabilities, strengths and weaknesses, and we are allowing them to mix and match their data warehouse environment with those technologies so they can achieve the right architecture.”
And further, when Teradata reaches out to Aster, said Birouty, “we refer to that as ‘analytics extensibility’ because what we have done is we make the Aster database and all its advanced functions look like an extension to the Teradata warehouse.”
“QueryGrid takes care of the technology underneath to make these different systems and different technologies work together in a way that the user is accustomed to,” said Birouty. “If I am user and I know how to use SQL, I can continue to use SQL to access all these other systems, or if I don’t really know how to use SQL, but I have nice BI front end from Tableau, MicroStrategy, or Business Objects, I can continue using that tool, and now I can access data and analytics on Hadoop, on Aster, on Oracle, on MongoDB - from the same tool. It puts the power in the user’s hands and allows them to access all of the data and analytics from all these other systems in the same way that they have always done.”
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