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HPE Data Fabric Software
HPE announces the next major release of HPE Data Fabric Software, advancing how enterprises access, manage, and govern data across a global data landscape. This release brings expanded global data access, AI-driven workflow capabilities, and simplified data management, helping organizations make trusted data readily available for AI and analytics workloads.
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HPE Data Fabric Anlyt Hadoop E‑LTU
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HPE Data Fabric Anlyt Spark E‑LTU
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HPE Data Fabric Bdl SSD E‑LTU
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HPE Data Fabric Bdl per Core E‑LTU
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HPE Data Fabric Cvg An Hadoop E‑LTU
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What's New
- AI-powered workflows: Use natural language to create, execute, and monitor data workflows, simplifying workflow orchestration and making it easier to manage data operations.
- Improved automated object movement: Simplifies automated data movement across distributed environments, making it easier to manage data across locations.
- Simplified installation: Installation and bootstrap enhancements simplify deployment and reduce the time and effort required to get Data Fabric up and running.
- Modern Spark support: Support for Apache Spark 4 and Spark Operator enables modern, scalable analytics workloads.
- Updated ecosystem support: Updated support for Apache Airflow 3.2.2, Apache Drill 1.22.0, and Livy 0.9 provides access to newer ecosystem capabilities.
- Expanded OS support: Support for SUSE Linux® Enterprise Server 15 SP7 and Ubuntu 24.04 provides greater flexibility for Data Fabric deployments.
Built for hybrid deployments
HPE Data Fabric Software can federate object and file data stores across on-premises, cloud, and edge environments and provide access through the global namespace, enabling connectivity and compute wherever the data resides.
A single user interface simplifies data management, security, and administration across multiple locations.
Built-in mirroring synchronizes data across locations to support availability, disaster recovery, and multi-site access.
Automated object movement enables real-time data movement across distributed S3-compatible environments to support data placement across locations.
Automated tiering with integrated lifecycle management and inline erasure coding helps reduce storage costs and improve efficiency.
Integrated global namespace
The built-in global namespace provides a single, consistent point of access, allowing users and applications to see and access enterprise data across distributed environments.
Unlocks the ability to optimize a customer's data landscape, reducing duplication and data movement and optimizing compute resources based on data affinity.
Accelerates insights by providing access to data across multiple enterprise systems without requiring data to be consolidated in a single location.
Extends data access across distributed environments while maintaining a consistent namespace across locations.
Integrates open table formats such as Apache Iceberg and external storage systems, enabling hybrid and multi-cloud data access.
Expanded metadata management capabilities
HPE Data Fabric Software captures and exposes metadata across the data landscape, providing greater visibility and context for data management, governance, and analytics.
Metadata federation enables visibility and governance across distributed data sources and environments.
Lakehouse metadata provides additional context for governance and cross-engine catalog visibility, improving lineage tracking, auditability, and policy enforcement.
Apache Polaris provides catalog capabilities across distributed environments, supporting metadata discovery, governance, and interoperability.
Makes metadata available to AI applications through MCP, supporting compliance, auditing, data discovery, and lineage use cases.
AI-powered data fabric
Combines AI with global data access and metadata to support AI-driven workflows and analytics across distributed enterprise data.
Model Context Protocol (MCP) provides a consistent interface for AI applications and agents to securely interact with data, metadata, and workflows.
Enables users and AI agents to create, execute, and monitor data workflows using natural language through Apache Airflow and MCP.
Integrated governance and compliance capabilities help ensure AI applications and workflows operate with appropriate data access, policies, and controls.
Extends zero trust principles to AI-driven workflows, enabling fine-grained, per-user governance and secure data access.
Linux is the registered trademark of Linus Torvalds in the U.S. and other countries.
All third-party marks are property of their respective owners.
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