HPE Ezmeral Data Fabric

Modern data management for your data-driven enterprise

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Solution overview

Accelerate business insights by operationalizing data and then exploit it across multiple use cases

  • Data related challenges

    Meaningful business insight comes from integrating and connecting data across multiple sources, tools, and technologies. Only then can you deliver the right data to the right place at the right time.

    Connecting data across multiple sources is an enormous challenge. Do you replicate it to different geographical locations? How can multiple use cases leverage the same data sets? How can you democratize data without impacting security, compliance, or locality regulations?

    Traditional data management solutions struggle to keep pace with the growth of data and the changing requirements of today’s digital enterprise. That’s because they don’t scale well, have complex infrastructures for each system, and require workforce with specialized management skillsets. As a result, delivery of business initiatives come with a set of large challenges that are time consuming and expensive.

    The digital enterprise is responding with data modernization initiatives that include a modern data fabric allowing them to:

    • Automate, curate, and orchestrate data across diverse sources

    • Accelerate fit-for-purpose insights to business and technical users with self-service data access

    • Enable global data sharing across peers, employees, partners, and customers

    • Deliver consistent, real-time data to build modern API-based cloud-to-edge applications

    Forrester reports that organizations without a data fabric strategy will spend more time and effort ingesting, integrating, curating, and securing their data.

  • HPE Ezmeral Data Fabric

    Just as a loom weaves multiple threads into fabric, a modern data fabric unifies data from any source into a single database and then democratizes it with self-service access to trusted data. A data fabric operationalizes data, so it can be used across multiple use cases and processes no matter where the data is located.

    HPE Ezmeral Data Fabric is a proven software-defined data store and file system with a strong track record across a wide variety of large-scale production environments. The founding vision was to make data-driven applications a reality for today’s digital enterprise by:

    • Supporting multiple data types, application programming interfaces (APIs), and ingest mechanisms

    • Enabling end-to-end artificial intelligence (AI)/machine learning (ML) workflows

    • Leveraging community innovation to handle a large and evolving set of tools and frameworks

    • Innovating data fabric technology

    • Accelerating containers and Kubernetes


Figure 1. HPE Ezmeral Data Fabric single platform

  • Universal data access

    One of the core tenets of HPE Ezmeral Data Fabric is an open platform that provides direct data access for legacy applications, modern analytics, and AI applications.

    Applications and users can use Hadoop Distributed File System (HDFS) or Portable Operating System Interface (POSIX)-based APIs. Developers can use Java, Python, SQL, Apache Spark, or Apache Hive queries. Data scientists can use the latest AI and ML tools, such as TensorFlow, H2O.ai, or PyTorch, reducing the need to copy data to a special-purpose system before it can be accessed. If your teams are familiar with Hadoop, they have access to the full range of Linux® commands without changing Hadoop or Spark programs (see Figure 1). The built-in Container Storage Interface (CSI) driver allows Kubernetes-based applications to directly access and manage data stored within HPE Ezmeral Data Fabric.


Figure 2. Access data in traditional ways or via modern APIs

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