Since its acquisition of ADIC in 2006, Quantum Corp. of San Jose, CA, appears to have done a better job than many other storage vendors in integrating the products of the acquired company into its portfolio. ADIC’s Scalar and StorNext products, in particular, are being marketed heavily since the deal and appear to be front and center in the company’s product development roadmap.
Most recently, Quantum released StorNext 3.0. This latest version extends data sharing to servers on the LAN and integrates data de-duplication into the software.
StorNext has been upgraded in three core areas. Data Reduction Storage (DRS) is a specialized disk tier that incorporates de-duplication. DRS tunes data reduction to a specific data set and increases the likelihood that very high levels of data reduction can be achieved. DRS is established on a local StorNext volume attached to the MetaData Controller (MDC), which serves as the traffic cop – handling disk allocation as well as client side buffering so that when multiple clients are reading or writing to/from the same file, they all see the same content. This architecture guarantees high throughput at FC speed rather than LAN speed.
“Data De-duplication reduces a customer’s data footprint, saves money by lowering capacity requirements and enables data to be retained on fast recovery disk for a much longer period of time,” says Nathan Moffitt, StorNext product manager at Quantum. “Data reduction rates of 10x or more can be achieved, depending on the data type and amount of data in the de-dupe volume.”
StorNext’s Storage Manager includes an integrated policy engine that automatically moves files from primary disk to one or more storage repositories (including tape). Thus data movement policies can also be established to manage the migration of files from primary storage to DRS and back. Further, primary disk can be freed up easily for high priority tasks.
Another addition to StorNext 3.0 is Dynamic Resource Allocation (DRA), which increases uptime by enabling online service operations. It allows customers to scale their storage – adding new storage capacity or transparently swapping out disk arrays during hardware upgrades – while the system is active.
DRA also enables rapid data sharing among servers by virtualizing the underlying storage components. A function known as File System Expansion allows capacity upgrades without disrupting business operations. Disk capacity can be added to an existing StorNext file system on the fly. The customer defines new LUNs and makes them available across the SAN to the MDC and StorNext clients. All I/O currently in progress remains unaffected during the expansion.
Another feature, Move Stripe Group Data, permits data to be moved from one disk volume to another. If, for instance, an array doesn’t have enough throughput or capacity, data can be quickly shifted onto another array.
This function can also be utilized to smoothly retire older arrays.
“StorNext can automatically move data from one stripe group to other stripe groups,” says Moffitt. “During migration, the file system is left online and read/write operations occur normally.”
Distributed LAN Client (DLC) is the third major area of StorNext upgrade. It enables applications on the LAN to access a shared pool of storage faster, and with a higher level of resiliency, than most traditional network sharing methods can provide. Using clustered gateways for access and an optimized communication protocol for performance, LAN Client extends data sharing, and delivers load balancing and transparent I/O failover.
“StorNext Distributed LAN Client allows LAN-based servers to connect to via clustered gateway systems,” says Moffitt. “To maintain the highest level of throughput, they only service LAN I/O and do not run applications.”
The LAN Client communicates with the MDC to determine file location, disk allocation and buffering. Once the LAN Client knows a file’s location, it passes on data request. The gateway system retrieves the data and passes it to the distributed LAN Client.
While similar to CIFS / NFS sharing used in NAS, DLC differs by utilizing a specialized TCP/IP protocol designed for higher per-stream throughput. Single GigE connections using LAN Client have been observed at 110 MBps, a marked improvement over NFS or CIFS.
Additionally, this protocol balances I/O across available gateways to avoid “hot spots” which could bottleneck throughput. It can also fail over I/O between gateways if one is unavailable.
All this adds up to an improved storage management platform for Quantum’s customers.
“Thousands of existing customers in the rich media and HPC markets rely on StorNext software for fast access to shared file systems, improved workflow and automated HSM,” says Brian Garrett, an analyst with the Enterprise Strategy Group of Milford, MA. “The new and improved StorNext will also be appreciated by enterprises looking for a better way to share and manage unstructured digital assets.”
This article was first published on EnterpriseITPlanet.com.
Ethics and Artificial Intelligence: Driving Greater Equality
FEATURE | By James Maguire,
December 16, 2020
AI vs. Machine Learning vs. Deep Learning
FEATURE | By Cynthia Harvey,
December 11, 2020
Huawei’s AI Update: Things Are Moving Faster Than We Think
FEATURE | By Rob Enderle,
December 04, 2020
Keeping Machine Learning Algorithms Honest in the ‘Ethics-First’ Era
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 18, 2020
Key Trends in Chatbots and RPA
FEATURE | By Guest Author,
November 10, 2020
FEATURE | By Samuel Greengard,
November 05, 2020
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 02, 2020
How Intel’s Work With Autonomous Cars Could Redefine General Purpose AI
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 29, 2020
Dell Technologies World: Weaving Together Human And Machine Interaction For AI And Robotics
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 23, 2020
The Super Moderator, or How IBM Project Debater Could Save Social Media
FEATURE | By Rob Enderle,
October 16, 2020
FEATURE | By Cynthia Harvey,
October 07, 2020
ARTIFICIAL INTELLIGENCE | By Guest Author,
October 05, 2020
CIOs Discuss the Promise of AI and Data Science
FEATURE | By Guest Author,
September 25, 2020
Microsoft Is Building An AI Product That Could Predict The Future
FEATURE | By Rob Enderle,
September 25, 2020
Top 10 Machine Learning Companies 2021
FEATURE | By Cynthia Harvey,
September 22, 2020
NVIDIA and ARM: Massively Changing The AI Landscape
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
September 18, 2020
Continuous Intelligence: Expert Discussion [Video and Podcast]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 14, 2020
Artificial Intelligence: Governance and Ethics [Video]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 13, 2020
IBM Watson At The US Open: Showcasing The Power Of A Mature Enterprise-Class AI
FEATURE | By Rob Enderle,
September 11, 2020
Artificial Intelligence: Perception vs. Reality
FEATURE | By James Maguire,
September 09, 2020
Datamation is the leading industry resource for B2B data professionals and technology buyers. Datamation's focus is on providing insight into the latest trends and innovation in AI, data security, big data, and more, along with in-depth product recommendations and comparisons. More than 1.7M users gain insight and guidance from Datamation every year.
Advertise with TechnologyAdvice on Datamation and our other data and technology-focused platforms.
Advertise with Us
Property of TechnologyAdvice.
© 2025 TechnologyAdvice. All Rights Reserved
Advertiser Disclosure: Some of the products that appear on this
site are from companies from which TechnologyAdvice receives
compensation. This compensation may impact how and where products
appear on this site including, for example, the order in which
they appear. TechnologyAdvice does not include all companies
or all types of products available in the marketplace.