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More Information

What's New

  • File Data Store is perfect when existing solutions cannot solve requirements for high data growth, new sites (edge, cloud, IoT) and/or new applications.
  • Distributed datastore for files and persistent storage for containers, cloud file migration and support for HDD and SSD.

Key Features

Flexible, All-Software Platform

Single data layer consolidates systems across locations and data types into a single view that reduces management complexity and costs.

Software defined scale-out storage and management speeds up ingestion, curation and analysis of data across core, cloud and edge.

Single infrastructure allows data to be managed as a single resource across files, table and data streams.

HPE Ezmeral Data Fabric provides storage and management choice without hardware lock-in.

Cost efficient monetization of large-scale data sets.

Global Namespace

Data clusters span geographic locations to deliver consistent file system structure to applications.

Scale-out file and object system across multiple physical and virtual clusters managed through one logical instance.

It delivers API-independent uniform access to files, tables and event streams even if data resides on multiple clusters in different locations.

Flexibility in tool and coding language choice to run legacy or modern applications on the same data layer and tenant.

Kubernetes persistent storage across all application workloads.

Resilient and Portable

Built-in mirroring simplifies data movement between and within clusters, geographic locations or secondary data centers for DR.

Ensures reliability and performance for very large clusters with self-healing capabilities without disruption of operations or system re-architecture.

Distributed metadata is a powerful design that protects against single or high-impact points of failure resulting in data loss.

To avoid congestion, the system reads from multiple replicas using multiple links or automatically moves data to avoid hotspots.

Directory, file, table and system metadata is copied as data is being replicated across a cluster.

Optimized for Scale

As data is being ingested, automatically grow storage capacity without impacting SLAs, reliability, downtime or IT intervention.

Designed to grow to very large-scale systems and still retain service levels for availability, performance and latency.

Automated storage tiering across hot, warm and cold layers optimizes utilization, cost and performance.

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* Prices may vary based on local reseller.

How can we help

Get advice, answers, and solutions when you need them. For general questions, email us at hpestore.quote-request@hpe.com

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