Table of Contents
The rise of hybrid and distributed environments—spanning on-premises, cloud, and edge—has redefined how enterprises manage and extract value from data.
Today, data is not just an asset; it is the foundation for intelligence, automation, and innovation. As organizations embrace AI and machine learning, the need for trusted, high-quality, and context-rich data has never been greater.
Overview
Market Overview
The rise of hybrid and distributed environments—spanning on-premises, cloud, and edge—has redefined how enterprises manage and extract value from data. Today, data is not just an asset; it is the foundation for intelligence, automation, and innovation. As organizations embrace AI and machine learning, the need for trusted, high-quality, and context-rich data has never been greater.
Traditional data architectures struggle to keep pace with these demands. The proliferation of data silos, inconsistent governance, and fragmented security models hinder visibility and slow decision-making. To compete in an AI-driven world, enterprises require a unified, intelligent data fabric—one that ensures secure access, consistent governance, and continuous insight across all environments.
The modern Data Lakehouse addresses these challenges by providing a single platform to store, process, and analyze structured and unstructured data at scale. When extended with AI-powered governance, policy automation, and metadata intelligence, it evolves into a true data fabric—enabling trusted analytics, accelerating AI adoption, and transforming data into a strategic differentiator.
Challenges of the Modern Data Landscape
Enterprises today face mounting challenges as data environments grow in scale, distribution, and complexity. Data sprawls across hybrid and multi-cloud infrastructures, often trapped in incompatible formats and isolated silos that limit accessibility and reuse. Managing this sprawl introduces operational friction—rising storage costs, inconsistent performance, and increased administrative overhead. Governance and compliance add further pressure, with regulations demanding granular visibility and auditable control across every data source. At the same time, emerging AI workloads require low-latency, high-context access that legacy systems were never designed to deliver. The result is a landscape where agility, trust, and efficiency are difficult to achieve—underscoring the need for a unified, intelligent data fabric that can seamlessly bridge these divides and enable AI-ready data operations at scale.
Product Overview
HPE Data Fabric Software is a next-generation data platform that unifies data management, governance, and intelligence across hybrid, multi-cloud, and edge environments. Designed for the AI-era, it transforms complex, distributed data ecosystems into a single, secure, and context-aware fabric—enabling organizations to access, govern, and utilize data with unprecedented efficiency and trust.
The platform provides a unified, location-independent view of data, simplifying access to files, objects, streams, and databases while maintaining enterprise-grade security and policy control. Integrated metadata intelligence supports advanced lineage, auditability, and governance—empowering teams to make informed, compliant, and timely decisions. It’s AI-powered control plane further automates data discovery, access, and compliance. This intelligent layer ensures data is consistently governed and readily available for both analytics and AI workloads. These capabilities form the backbone of a modern data platform that simplifies operations while driving greater business agility.
In essence, HPE Data Fabric Software delivers measurable cost savings and productivity gains by consolidating data from on-premises, cloud, and edge environments into a single logical store. By minimizing data movement and duplication, it optimizes resource utilization and operational efficiency—allowing businesses to focus on innovation rather than administration, and to accelerate their journey toward data-driven and AI-enabled outcomes.
Business Outcomes
Drives Business Agility with Data Lakehouse: HPE Data Fabric Software enables organizations to create a robust data lakehouse that supports structured and unstructured data, facilitating advanced analytics. This vendor-agnostic, location-independent solution drives business agility by simplifying the integration of new technologies and promoting data reuse across various projects, resulting in cost savings and increased efficiency.
Accelerates Data-Driven Insights: By unifying diverse data types such as files, objects, NoSQL databases, and real-time/batch streams into a unified data backbone, HPE Data Fabric Software provides a comprehensive view of data crucial for analytics, AI, and ML initiatives. This unified data environment empowers businesses to rapidly identify trends, anomalies, and relevant datasets for faster decision-making and strategic planning.
Streamlines Data Access & Management: HPE Data Fabric Software simplifies data management and control with a single pane of glass view and a global namespace for effortless data discovery, for data across multiple locations and formats, including on-premise, public cloud, and edge devices. By providing a comprehensive 360-view of your data landscape, HPE Data Fabric Software ensures streamlined data governance, improves compliance with data security and privacy regulations.
Hybrid Security Simplified: HPE Data Fabric Software seamlessly integrates with existing IAM systems for authentication and authorization, offering a single security management system for hybrid environments. This integration, along with advanced features like automated policy management, minimizes risks associated with manual security management and reduces the cost.
Improved Intelligence with Advanced Analytics Support: HPE Data Fabric Software supports continuous intelligence and advanced analytics through seamless integration with certified open-source tools and offers native support for CSI drivers and other HPE containerization platforms. By leveraging NVIDIA GPU Direct technology, the software accelerates AI and machine learning workloads, ensuring optimal performance, scalability, and data-driven innovation for businesses seeking to enhance operational efficiency and decision-making.
Enables AI-Ready Operations: Through its AI-powered control plane and intelligent metadata governance, HPE Data Fabric establishes a trusted foundation for next-generation AI workloads. Data remains discoverable, governed, and context-rich—allowing enterprises to operationalize AI securely and at scale with confidence and agility.
What’s New:
HPE Data Fabric 8.0 introduces next-generation capabilities that unify AI interoperability, strengthen metadata intelligence, and extend real-time analytics across the hybrid data landscape.
- – AI-Powered Fabric (Model Context Protocol Integration) – Embeds a built-in MCP server to enable secure, zero-trust model-to-data connectivity and seamless interoperability with any MCP-compliant AI tool or framework. This foundation empowers organizations to operationalize AI governance, compliance, and automation natively within the fabric.
- – Enhanced Metadata Intelligence with Apache Polaris– Integrates Apache Polaris forunified metadata governance and cross-engine catalog visibility, improving lineage tracking, auditability, and policy enforcement across the Lakehouse ecosystem.
- – Apache Flink Integration for Real-Time Analytics – Introduces native Flink support for high-velocity data processing and streaming analytics, enabling faster event-driven insights and powering next-generation AI and operational workloads.
Standard Features
Feature Set for HPE Data Fabric Software
Global Namespace
- – Global view of all data sources (on-prem, cloud, edge)
- – Federated sources, NFS, and S3
- – Unified authentication policy & security
- – Optimized cloud deployment (AWS, GCP, Azure)
- – Iceberg with Polaris support
- – NVIDIA Direct Support
Data Management:
- – Support for files and objects
- – Event Streams
- – NoSQL Database
- – Data Tiering: Hot (default), Warm (Erasure coded), and Cold (off-load to external stores)
- – Support for NVMe, SSD, and HDD
- – Mirroring and snapshots
Data Access:
- – POSIX client (unlimited client instances)
- – NFSv4 and NFSv3
- – HDFS and HTTPFS APIs
- – S3 API
- – Kafka compliant streams API
- – NoSQL databases for analytics and operational applications: a key-value database with HBase API and a JSON document database with OJAI
- – Container Client including PACC, CSI (unlimited client instances)
- – Model Context Protocol (MCP) Server
Core Data Capabilities:
- – Resiliency and self-healing
- – Auto-balancing
- – Multi-site volume mirroring
- – Volume Mirroring for Disaster Recovery
Performance and Optimization:
- – Data Topologies
- – Compression
- – Multiple file server instances per node
Administration and Security:
- – Administration using CLI, REST, GUI
- – Rolling upgrades
- – UI Installer
- – Quotas
- – Multi-tenancy (not for Object Store)
- – Insights Service to track user behavior
- – Unified security including authentication, authorization, wire and data-at-rest encryption
- – Unified roles
- – User-managed roles
- – IPv6 support
HPE Data Fabric Software Supported Data Formats
Files: A distributed file system designed to handle structured and unstructured data with reliability and scalability. It features patented capabilities that ensure data protection and efficient storage management for diverse data types.
Object Store: A native object storage solution designed to efficiently manage objects and metadata for optimized access. As a fully S3-compliant storage system, it provides seamless integration with applications that require compatibility with S3 sources.
NoSQL Databases: Two databases for analytics and operational applications
- – Columnar (Key-value) Database: Columnar Database is supported on the platform, and you can use HBase API to interact with this data.
- – JSON Document Database: JSON document database is supported on the platform and one can use OJAI API to interact with the data.
Event Streams: A built-in publish-and-subscribe messaging system that supports Kafka APIs. It enables seamless integration without the need for additional process management, making it an ideal choice for real-time data processing and event-driven applications.
HPE Data Fabric 8.0 Add-on options:
HPE Data Fabric Analytics for Apache Spark
Spark 3.5.1.0: Upgraded Spark version in Ecosystem Pack (EEP 9.3.0) to enhance large-scale data processing and analytics capabilities within Data Fabric, supporting advanced machine learning, graph processing, and real-time streaming applications.
HPE Data Fabric Analytics Premium Package
Includes Spark, Hadoop, Drill, Apache Ranger, and Apache NiFi, providing a comprehensive suite of tools for data management, processing, analytics, and security within the Data Fabric ecosystem.
Apache Hadoop 3.3.5.400
Offers distributed storage and processing capabilities for large datasets across clustered systems within the Data Fabric environment.
Apache Drill 1.20.3.3001
Provides a powerful SQL query engine for Data Fabric users to explore and analyze large-scale datasets, enabling interactive analytics and data exploration on Hadoop-based systems.
Apache Hive 3.1.3.600
Simplifies data analysis and manipulation operations within Data Fabric, allowing users to read, write, and manage large datasets using SQL-like queries.
Apache Airflow 2.9.1.0
Facilitates the creation, management, and scheduling of complex data pipelines within Data Fabric by enabling users to define and execute Directed Acyclic Graphs (DAGs) of tasks using Python.
Apache Ranger 2.4.0.0
Ensures data protection and compliance across diverse data sources and applications within Data Fabric through centralized security administration and access control.
Apache NiFi 1.19.1.100
Offers efficient data management for Data Fabric users by providing a robust data integration and processing platform that supports dataflow automation, stream processing, and real-time data ingestion.
Apache Flink 2.0.0
Delivers real-time stream processing and event-driven analytics through a distributed processing engine that enables low-latency insights and continuous data computation at scale.
For more details see: https://docs.ezmeral.hpe.com/datafabric-customer-managed/78/c_ecosystem_intro.html
HPE Data Fabric File and Object Store Capability Matrix | |
|---|---|
| Capabilities | HPE Data Fabric File and Object Store |
| Distributed File and Object store | Yes |
| Unified security including authentication, authorization, policy-based security, external KMIPkeystore, and encryption (on-wire & at-rest) | Yes |
| Support compression, auto-balancing, resilient through replication | Yes |
| Highly scalable, global namespace, quotas, auditing, rolling upgrades | Yes |
| Data topologies, data tier support: 'hot' for fast data; 'warm' for Erasure coded and 'cold' to offload data to 3rd party S3-based external stores. | Yes |
| Container Client including PACC, Flex Volume Plugin, CSI (unlimited client instances) | Yes |
| Snapshots and mirroring of data across clusters (used for data safety, access from multiple geo locations and disaster recovery) | Yes |
| Operating systems supported: RHEL, SUSE, Ubuntu and Oracle Enterprise Linux | Yes |
| Management using CLI, REST and GUI | Yes |
| Support for NVMe, SSD & HDD | Yes |
| Support for NFSv4 & NFSv3 | Yes |
| Clients - Hadoop for MapR-FS, HTTP-FS | Yes |
| Multiple file server instances per node | Yes |
| Supports the following for File store only:
| Yes |
| Supports the following for Object store only:
| Yes |
| HPE Data Fabric Installer | Yes |
| HPE Data Fabric Monitoring | Yes |
| Hive Metastore | Yes |
| Apache Ranger
| Yes |
| HPE Data Fabric Event Data Streams:
| Yes |
| HPE Database:
| Yes |
| HPE Data Fabric Event Data Streams:
| Yes |
HPE Data Fabric for Analytics Capabilities Matrix | ||
|---|---|---|
| Capabilities | HPE Data Fabric Analytics for Apache Spark | HPE Data Fabric Analytics Premium Package |
| Apache Spark Ecosystem:
| Yes | Yes |
| GPU based acceleration | Yes | Yes |
| SQL ecosystem with Drill:
| | Yes |
| Hadoop Ecosystem
| | Yes |
| Apache Airflow | | Yes |
| Apache NiFi | | Yes |
| Apache Zeppelin | | Yes |
| Apache Livy | | Yes |
| Apache Tez | | Yes |
| Model Context Protocol (MCP) Server | | Yes |
| Polaris Catalog | | Yes |
| Apache Flink | | Yes |
Service and Support
Consume IT on your terms
HPE GreenLakebrings the cloud experience directly to your apps and data wherever they are—the edge, colocations, or your data center. It delivers cloud services for on-premises IT infrastructure specifically tailored to your most demanding workloads. With a pay-per-use, scalable, point-and-click self-service experience that is managed for you, HPE GreenLake accelerates digital transformation in a distributed, edge-to-cloud world.
- – Get faster time to market
- – Save on TCO, align costs to business
- – Scale quickly, meet unpredictable demand
- – Simplify IT operations across your data centers and clouds
Managed services to run your IT operations
HPE GreenLake Management Services provides services that monitor, operate, and optimize your infrastructure and applications, delivered consistently and globally to give you unified control and let you focus on innovation.
HPE software services
HPE Hybrid Cloud Professional Services provide expert consulting, implementation, and support to help organizations harness the power of HPE’s Data Fabric platform. These services are designed to simplify data management, accelerate analytics, and enable seamless data integration across hybrid, edge, and multi-cloud environments. The goal is to help businesses unlock the value of their data for improved decision-making and operational efficiency. HPE Hybrid Cloud Professional Services are tailored to help businesses modernize their data ecosystems, improve operational efficiency, and unlock the full potential of their data assets. Whether for analytics, AI, IoT, or hybrid cloud management, these services provide the expertise and support needed to succeed in today’s data-driven economy.
Key Offerings include:
Assessment and Planning
- – Data Architecture Review: Evaluate current data systems and recommend an optimal architecture for implementing HPE Data Fabric.
- – Migration Planning: Create a roadmap for transitioning from legacy systems to HPE Data Fabric with minimal downtime.
Design and Implementation
- – Data Fabric Deployment: Design and implement an HPE Data Fabric solution to meet specific business needs.
- – Data Integration: Enable seamless integration of disparate data sources, including cloud, on-premises, and edge systems.
- – Hybrid and Multi-Cloud Enablement: Configure the HPE Data Fabric to support hybrid and multi-cloud architectures for enhanced flexibility.
Optimization, Modernization & Migration
- – Performance Tuning: Optimize HPE Data Fabric configurations for better performance and scalability.
- – Modernization Services: Upgrade existing data systems to an HPE Data Fabric solution to improve efficiency and reduce costs.
- – Advanced Analytics Support: Design, develop and deploy pipelines and tools for real-time and batch analytics to empower data-driven insights.
- – Migration: Assist with migrating from legacy systems or other platforms to HPE Data Fabric.
HPE Hybrid Cloud Platform Services
- – Proactive Monitoring and Support: 24X7 monitoring and proactive management to ensure high availability and performance.
- – Capacity Planning: Support for scaling storage and processing capabilities as business needs grow.
HPE training
HPE data and analytics training delivers the skills and expertise for success with Big Data, containers, AI/ML and deep learning—including HPE Data Fabric. Live virtual instructor-led and eLearning courses are available.
HPE Support Services are sold by Hewlett Packard Enterprise and Hewlett Packard Enterprise Authorized Service Partners:
- – Services for customers purchasing from HPE or an enterprise reseller are quoted using HPE order configuration tools.
- – Customers purchasing from a commercial reseller can find HPE Support Services at
Configuration Information
Ordering Information
HPE Data Fabric File and Object Store subscriptions include an electronic license to use on one terabyte of storage, Customer's license capacity under management is defined in the Additional Licensing Authorizations (ALA) for
Notes:
- – Each subscription SKU includes a term license to use on one core plus the associated 24x7 HPE Tech Care support.
- – HPE Data Fabric is licensed by the number of unique cores available to the kernel in the OS on which the HPE software is directly installed, regardless of the number of threads in each core.
All HPE Data Fabric Software subscriptions include support with 24x7 coverage.
HPE Services HPE Tech Care Service
HPE Services HPE Tech Care Service is the operational service experience for HPE products. Tech Care goes beyond traditional support by providing access to product specific experts, an AI driven digital experience, and general technical guidance to not only reduce risk but constantly search for ways to do things better. HPE Services HPE Tech Care Service has been reimagined from the ground up to support a customer-centric, AI driven, and digitally enabled customer experience to move your business forward.
HPE Data Fabric Software products are covered by HPE Services HPE Tech Care Service Essentials, providing 24x7 global support coverage.
Notes:
- – The following end user information is required at the time of order to receive the electronic license:
- End-user organization name
- End-user organization address
- End-user contact name
- End-user email address
- Reseller and distributor organization name and address
HPE Data Fabric Software Subscription OptionsSKUs are available in HPE’s new BRIM subscription ordering system as well as the traditional S4 ordering system. Please work with the Sales Team to determine which is the best system for placing your order. | |
| BRIM | |
| Description | SKU |
| HPE Data Fabric File Object E-LTU | R9J44AAE |
| HPE Data Fabric Anlyt Spark E-LTU | R9J45AAE |
| HPE Data Fabric Anlyt Prem Pk E-LTU | R9J47AAE |
| S4 | |
| Description | SKU |
| HPE Data Fab Fl Obj Store 1yr 24x7 E-LTU | S0M33AAE |
| HPE Data Fab Fl Obj Store 2yr 24x7 E-LTU | S0M52AAE |
| HPE Data Fab Fl Obj Store 3yr 24x7 E-LTU | S0M34AAE |
| HPE Data Fab Fl Obj Store 4yr 24x7 E-LTU | S0M35AAE |
| HPE Data Fab Fl Obj Store 5yr 24x7 E-LTU | S0M36AAE |
| HPE Data Fabric Spark 1yr 24x7 E-LTU | S0M37AAE |
| HPE Data Fabric Spark 2yr 24x7 E-LTU | S0M38AAE |
| HPE Data Fabric Spark 3yr 24x7 E-LTU | S0M39AAE |
| HPE Data Fabric Spark 4yr 24x7 E-LTU | S0M40AAE |
| HPE Data Fabric Spark 5yr 24x7 E-LTU | S0M41AAE |
| HPE Data Fabric Prem Pckg 1yr 24x7 E-LTU | S0M47AAE |
| HPE Data Fabric Prem Pckg 2yr 24x7 E-LTU | S0M48AAE |
| HPE Data Fabric Prem Pckg 3yr 24x7 E-LTU | S0M49AAE |
| HPE Data Fabric Prem Pckg 4yr 24x7 E-LTU | S0M50AAE |
| HPE Data Fabric Prem Pckg 5yr 24x7 E-LTU | S0M51AAE |
| Learn More:
| |
Summary of Changes
| Date | Version History | Action | Description of Change |
|---|---|---|---|
| 03-Nov-2025 | Changed | Overall updates have been made to reflect brand updates across all aspects of the product. | |
| 28-Jul-2025 | Changed | Update survey link. | |
| 07-Apr-2025 | Changed | Overview section was updated | |
| 17-Mar-2025 | Changed | QS name updated | |
| 02-Dec-2024 | Changed | Overview, Standard Features, Service and Support and Configuration Information sections were updated. | |
| 07-Nov-2022 | Changed | Overview, Standard Features, Service and Support and Configuration Information sections were updated. | |
| 15-Aug-2022 | Changed | Service and Support and Configuration Information sections were updated. | |
| 01-Aug-2022 | Changed | Service and Support and Configuration Information sections were updated. | |
| 02-May-2022 | Changed | Overview and Configuration Information sections were updated. | |
| 15-Nov-2021 | Changed | Service and Support section was updated | |
| 06-Apr-2021 | Changed | Overview and Configuration Information sections were updated. | |
| 01-Mar-2021 | Changed | Overview, Standard Features, Service and Support and Configuration Information sections were updated. | |
| 01-Feb-2021 | New | New QuickSpecs |
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