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August 29, 2017
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Denodo Platform 6.0 Certification with HDP 2.5

This guest blog is from our partner Denodo who is a leader in data virtualization and a Hortonworks partner for many years. Denodo helps customers who have data from multiple, heterogeneous sources to quickly, easily and cost-effectively integrate it to derive business insights and positively change their strategy to become more data-driven. In addition to earning HDP certification, Denodo has earned YARN Ready and Security Ready badges, demonstrating their integration with YARN, and their focus on data security and governance. We are happy to have them join our team of certified technology providers and deliver exceptional value to our mutual customers.

In this blog, Ravi Shankar, CMO at Denodo, describes the platform and how it supports Hortonworks Data Platform.

Inside the Denodo Platform

The Denodo Platform uses data virtualization to provide analysts with real-time access to data across Hadoop and myriad other traditional and NoSQL repositories. Rather than physically moving the data, data virtualization creates integrated views of the data, and makes them available to a plethora of consuming applications. This not only enables queries and reports that cut across the disparate sources, but also modern architectures like virtual data marts and logical data warehouses, which present the disparate sources as if they sit in the same repository. Data virtualization abstracts analysts from the complexities of where the data is actually stored and the particularities of access.

Putting the Platform through the Paces

In 2015, after a series of rigorous, real-world tests using a live Hadoop cluster as a data source, involving data ingestion, data transformation, and data analysis, Hortonworks initially certified Denodo Platform 5.5 on Hortonworks Data Platform (HDP) 2.1. Most recently, Hortonworks certified the latest version of the Denodo Platform, 6.0, on HDP 2.5, demonstrating that the Denodo Platform flawlessly interoperates with the Hortonworks implementations.

The Denodo Platform can support Hortonworks Data Platform implementations in three ways:

  1. Querying Hadoop through Hive. Since Hive makes Hadoop clusters appear as relational databases, The Denodo Platform can query a Hadoop cluster, through Hive, applying all manner of query optimization techniques. For large queries, the Denodo Platform pushes down the query processing to the source, and sends back just the results, for greatly accelerated performance.
  2. Accessing Hadoop directly. Here, since we are dealing with unstructured data, the Denodo Platform cannot process queries, but can retrieve files using APIs. During the certification process, the new features of Denodo Platform 6.0, such as self-service data discovery capabilities and advanced monitoring and diagnosis tools, were successfully tested using the latest APIs, as of the release of Hortonworks 2.5.
  3. Ranger Support. Denodo Platform 6.0 supports Apache Ranger, the trusted security framework for Hadoop, using standard Kerberos protocols and user impersonation. This enables stakeholders to design, implement, and enforce granular security rules, including credential-driven access privileges, across multiple data sources from a single point of control.

By achieving certification on HDP 2.5, and earning three Partnerworks badges (HDP Certified, Yarn Ready, and Security Ready), Denodo Platform 6.0 proves itself capable of working seamlessly with HDP to enable the latest architectures for getting the most out of big data investments.

Learn More

To learn more about how the Denodo Platform and Hortonworks can work together to enable significant benefits, please see the Denodo/Hortonworks Solution Overview brief.

Visit Hortonworks – Denodo page on

Visit Denodo – Denodo is the leader in data virtualization, providing agile, high performance data integration and data abstraction across the broadest range of enterprise, cloud, big data and unstructured data sources, and real-time data services, at half the cost of traditional approaches.

Comments says:

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