Unify Data Silos. Build a Data Hub.

Storing data in data lakes and silos is so 2008. To compete in today’s economy, organizations must unify their data and then analyze it for intelligence and advantage. For that, there’s data hub.

Data Hub Meets Today’s Challenges

A data hub is a modern, data-centric architecture for storage – powering analytics and AI by enabling enterprises to consolidate and share data in today’s data-first world. Unlike data lake and legacy DAS architectures engineered primarily to store data, a data hub is designed to share data.

CONSOLIDATE DATA SILOS

Eliminate infrastructure complexities with a single data platform built to move at the speed of your data.

UNIFY AND SHARE DATA

Drive intelligence by putting all of your data to work. In business today, shared data is far more valuable than stored data.

ACCELERATE APPLICATIONS

Push the limits of your data with storage built to serve data concurrently, and forget legacy silos built only to store data.

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“Enterprises in every industry are working to build their future with AI. The data hub architecture will assist customers in modernizing their storage infrastructure to maximize the compute power required for AI.”

Jim McHugh, VP and GM of Deep Learning Systems
NVIDIA

FOUR ESSENTIAL FEATURES OF A DATA HUB

A data hub takes the key strengths of the four analytics silos – data warehouse, data lake, streaming analytics, and AI clusters – and integrates them into a single, unified platform. Any true data hub must have these four features.

HIGH THROUGHPUT FILE & OBJECT

Backup and data warehouse apps need high throughput to speed queries and analytics.

SEAMLESS, NATIVE SCALE-OUT

Data lake redefined as scale-out infrastructure, enabling applications to run at any scale.

MULTI-DIMENSIONAL PERFORMANCE

Streaming analytics requires storage to drive any data, small or large, with any I/O pattern.

MASSIVELY PARALLEL ARCHITECTURE

AI clusters, with 1000s of cores and GPUs, need storage to be massively parallel as well.


FAREWELL,
DATA LAKE

The contrast between a data lake and a data hub is profound. A data lake is designed to store data. A data hub is designed to share and deliver data. The former is engineered with legacy DAS-based technologies. The latter is a modern system based on an all-flash, cloud-like architecture. Data is today’s challenge; a data hub is today’s solution.

INDUSTRY’S FIRST DATA HUB FOR STORAGE

FlashBlade is one of the most advanced scale-out storage solutions ever built. It’s a true data hub driven by a ground-breaking software engine – Purity//FB – built from the ground-up to bring the power of all-flash at every layer of software.

GIVE DATA TEAMS WHAT THEY NEED – DATA

Data is the fuel enabling data scientists and engineers to deliver on the new possibilities of analytics and AI. But the storage industry’s legacy architectures have inhibited progress. A data hub is here to finally break through those data silo barriers.

SEE DATA HUB DRIVE ANALYTICS AND AI

What if all your analytics applications could run on a single data platform capable of delivering real-time performance? It’s now possible – with a data hub. Watch as we index and analyze a Twitter feed using industry tools like Solr, Hadoop, and Spark. We then showcase the power of a data hub by applying AI to detect objects using the same dataset.

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“FlashBlade functions as a dynamic data hub, built to support all types of data loads, and that is exactly what we need to meet client demands.”

Dan Otterness, Infrastructure Manager
Allant Group
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“A 10x-20x improvement in performance can be a game-changer when it comes to creating a time-to-market competitive advantage for us.”

Gary Collier, CTO
Man AHL
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“Data Hub is the vision for a new storage architecture designed for this evolution, purpose-built to power the next generation of AI products.”

Jean-Francois Gagne, Founder and CEO
ElementAI

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