HPE fuels data-driven digital transformation with new products and partnerships for HPE Ezmeral Software

Hewlett Packard Enterprise announced advancements to the HPE Ezmeral software portfolio, with new products and partnerships designed to help organizations unify access to data, from edge to cloud, to fuel their digital transformation initiatives. Together, the HPE Ezmeral portfolio provides customers with an end-to-end hybrid cloud analytics platform that improves quality, repeatability, throughput, and time to value for their AI/ML, analytics and data-intensive workloads. 

Today’s updates include the following:

• HPE Ezmeral Data Fabric – Now available as a standalone offering in addition to being available as an integrated component of the HPE Ezmeral Container Platform and HPE Ezmeral Machine Learning Operations (ML Ops). The HPE Ezmeral Data Fabric brings a persistent storage layer to streamline the entire machine learning model lifecycle across on-premises, public cloud, hybrid cloud, and edge environments.

• A new HPE Ezmeral Technology Ecosystem program, which includes industry leading ISVs  such as Dataiku, MinIO, H2O.AI, Rapt.AI, Run:AI, Sysdig, and Unravel,  that have validated their applications on HPE Ezmeral, allowing customers to more rapidly create streamlined analytics environments.

• A new HPE Ezmeral Marketplace available to customers that brings the top ISVs and open-source projects such as Apache Spark, Tensorflow, and many more, to enterprises looking to modernize their workloads to be cloud-native.

The HPE Ezmeral Data Fabric is ideal as the global file system foundation for large scale custom applications, a data lake for analytics applications, and software-defined storage for large scale container environments. It is now available as a software-defined, scale-out data store to help solve challenges for data-intensive applications from edge to cloud. Additionally, as organizations look to modernize their enterprise workloads, the HPE Ezmeral ecosystem brings the top open-source projects and ISVs together for access to the data and tools enterprises prefer, all in one control plane for the entire data science team.

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