Hortonworks Updates Its Data Platform and Expands Partnerships

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Hortonworks today launched the latest version of its Hortonworks Data Platform as well as expanded partnerships with Google, Microsoft, and IBM.

“Customers are going to run stuff on-premises and customers are going to run stuff on the cloud; we want to give them the best-of-breed experience in both places,” says Arun Murthy, cofounder and chief product officer at Hortonworks.

Hortonworks Data Platform 3.0 aims to enable organizations to derive value from their data more quickly, reliably, and securely. To that end, the latest version of the Apache Hadoop-based platform delivers four key enhancements, all of which are based on Apache Hadoop 3.1.

First, it offers containerization, enabling apps to be launched quickly, with the goal of saving time and resources for users.

Second, it allows users to easily run workloads that require GPU resources, such as deep learning, via pooling and isolation that enable data scientists to democratize and share GPU access.

Third, it features a real-time database that unifies the performance gap between low-latency and high-throughput workloads with the goal of providing improved query optimization and, ultimately, to process more data at a faster rate.

Fourth, it has enhanced security and governance aimed at increasing regulatory compliance. More specifically, it allows users to track data from its origin to the data lake, and it enables auditors to view data without making changes, implement time-based policies, and audit third party-events with encryption protection.

Hortonworks' expanded partnerships allow for a range of new integrations and functionality. Due to the expanded partnership with Google, for instance, Hortonworks Data Platform and Hortonworks DataFlow now integrate more deeply with Google Cloud Platform. As a result, Hortonworks Data Platform integrates with Google Cloud Storage, providing customers with two key benefits: First, on-demand analytics workloads can be deployed in minutes; second, Apache Hive and Apache Spark can be utilized for interactive query, machine learning, and data analytics.

And the integration between Hortonworks DataFlow and Google Cloud Platform enables customers to easily and securely move data flows between on-premises and Google Cloud Platform deployments, as well as build streaming applications in a matter of minutes to capture insights in real time without needing to write code.

In addition, the expanded partnership simplifies the deployment of both Hortonworks Data Platform and Hortonworks DataFlow on Google Cloud Platform, with the goal of making it easy for customers to configure and secure workloads for the cloud while optimizing their use of cloud resources.

As for the expanded partnership with Microsoft, customers can deploy Hortonworks Data Platform, Hortonworks DataFlow, and Hortonworks DataPlane Service products natively on Microsoft Azure infrastructure-as-a-service, with the goal of helping them derive value from data of all types. It also allows customers to use Microsoft Azure HDInsight, a service powered by Hortonworks Data Platform that delivers Apache Hadoop and Apache Spark.

Finally, the expanded alliance with IBM has yielded IBM Hosted Analytics with Hortonworks, an integrated solution-as-a-service on the IBM Cloud that provides users with a data management and analytic environment via the cloud. IBM Hosted Analytics with Hortonworks brings together Hortonworks Data Platform, IBM Data Science Experience, and IBM Big SQL.

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