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Hortonworks proudly announces the eagerly awaited full release of its data platform,  Hortonworks Data Platform 3.0. With businesses becoming more data-driven, Hortonworks Data Platform 3.0 (HDP 3.0) is a major footstep in the plan for dominating the Big Data ecosystem. They’ve made major changes within its stack and expanded their ecosystem to include trending technologies like Deep Learning.

With the GA release, HDP 3.0 equips businesses with enterprise-grade functionalities, enabling speedy application deployment, managing machine learning workloads with real-time database management. The platform is designed to provide complete security and governance for your business applications. The data platform is added with additional support to GPU computing, containerization, Namenode Federation and Erasure Coding and all these new features are developed on Hadoop 3.1. The platform supports both on-premise and cloud deployment including major cloud platforms such as Amazon Web Services, Microsoft Azure, and Google Cloud. The platform is also stocked with Apache Ranger and Apache Atlas to provide a secure and trusted Data Lake infrastructure.

To keep the stack intact and smooth, the new release has deprecated various Apache components like Falcon, Mahout, Flume and Apache Hue.

Key features of HDP 3.0:

Agile Application Deployment: It enables application developers to deploy their applications using containerization technology. With this, developers can test new versions and at the same time can create new features without damaging the old ones. This feature results in speedy application deployment along with optimum utilization of resources at hand.

Deep Learning Support: With Deep Learning technology becoming the backbone of today’s intelligence, HDP 3.0 provides complete support for GPU computing and deep learning workloads. The platform provides both GPU pooling and GPU isolation support through which GPU resources can be used at the optimal level and at the same time can be used exclusively for a specific application based on its priority and complexity level.

Cloud Optimization: It is accelerated with automated cloud provisioning for simpler deployment of big data applications with support to major cloud object stores such as Amazon S3, Azure Data Lake, and Google Cloud Storage. The platform also provides speedy query performance with the support of cloud connectors including Apache HBase and Apache Spark.

This newly revamped and innovated big data platform can help businesses achieve faster insights and with decision-making in today’s competitive business environment.

For more detailed information on the HDP 3.0, please visit the official product page.

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Category Manager and tech enthusiast. Previously worked on global market research and lead generation assignments. Keeps a constant eye on Artificial Intelligence.


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