Hammerspace Global File System

The Hammerspace global file system is built for the hybrid cloud to universally deliver software defined storage services for file data on any infrastructure, in any cloud…anywhere.

Overcome silos to modernize hybrid cloud data workflows

Multi-site, multi-cloud

All data is accessible active-active across all sites through a universal global namespace, virtualized and replicated at file-level granularity.

Non-disruptive

Zero-downtime assimilation quickly brings data online, while live data mobility eliminates migration disruptions.

File granular data management

Managing data at file-level granularity is the only way to efficiently scale across complex mixed infrastructure without creating unnecessary copies of entire volumes of data.

Native Kubernetes support

Deliver enterprise data services for persistent data in Kubernetes across any available storage.

Software defined

Available in cloud marketplaces and on-premises as software-only deployments.

Automate orchestration by business objectives

Extensible user-defined metadata describes objectives and machine learning driven automation tiers data across storage, sites and clouds.

Scale beyond cloud

Simplify performance and capacity planning with a true parallel, scale-out filesystem with direct data access.

Use any storage

Run on any NAS, commodity, or cloud service infrastructure.

Predictive cost profiling

Analyze the available storage infrastructure and behavior of data to predict the cost of different tiering scenarios.

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Enterprise Data Services Built for Hybrid Cloud

Data virtualization

Hammerspace separates the control plane (metadata) from the data plane (data) so that data can be managed independently from the infrastructure. By managing metadata separately from data, it becomes possible to make file data virtually appear anywhere without copying it over.

Global undelete

Undelete empowers end-users to be more productive by extending the ability to self-service their recovery from data loss.

Intelligent data tiering

Machine learning automates the tiering of data across different storage infrastructure on-premises or the cloud based on a variety of performance, cost, location, or any other metadata available. Data is moved live and in real-time to meet business SLAs and avoid potential bottlenecks.

Data replication

Protect data over geographical distance and into the cloud with Hammerspace to create multiple copies of data without sacrificing performance.

Universal global namespace

Present data at all sites as if it were local, without copying, using an active-active filesystem namespace that runs on any storage system or cloud.

Global dedupe & compression

Data stored in cloud storage is automatically deduplicated and compressed for faster replication and lower bandwidth usage. Take advantage of global data reduction technology to keep capacity costs low across all sites, on-premises and the cloud.

Real-time analytics

Machine learning continuously optimizes data across the infrastructure for cost and performance. Behavior is analyzed and reported through dashboards and APIs.

Open protocol standards

NFS, SMB, S3, and CSI support.

Data-in-place assimilation

Hammerspace data services extend to data stored on existing NAS storage infrastructure without having to first copy data into Hammerspace. Get started in minutes with billions of files and unlimited capacity.

Share-level snapshots

Centrally manage global snapshots with granular controls, throughout their life-cycle. Offload snapshots to the cloud to reduce tier-1 storage needs and increase resiliency of data. Supports daily snapshot per share for up to 7 years to meet long-term compliance needs without sacrificing granular recovery needs.

Live data mobility

Hammerpace non-disruptively moves data live, even when it is being read/written to, between storage systems, sites, and clouds.

Extensible metadata

Extensible metadata allows for user-defined metadata (keywords and tags) as well as pre-declared entries (labels and attributes) to be added to the file system. Users can view, filter and search meta- data in-place while navigating the namespace. Rather than relying on filenames to identify data, user-defined metadata rapidly, accurately, and efficiently enables users to find the data they need.