Big Data. Big Decisions
InformationWeek
Special Coverage Series


Sepaton Upgrades Backup Appliances

Sepaton DeltaStor also includes support for multi-streamed, multiplexed database backup.

The Best of Interop 2012
The Best of Interop 2012
(click image for larger view and for slideshow)
Sepaton on Wednesday introduced new software for its S2100-ES2 and S2100-DS3 backup appliances that support multi-streamed, multiplexed database backups that it said would not affect the performance of the backup or recovery of data. The company also added support for Symantec NetBackup OpenStorage features including A.I.R., Optimized Synthetics, Accelerator, and Granular Recovery Technology.

The company's new DeltaStor DBeXstream technology now includes support for multi-streamed, multiplexed Oracle, DB2, and SQL Server databases for fast backup and restore performance while also maintaining high data deduplication ratios. The new technology allows as many as 16 simultaneous streams or channels to be backed up just like a database administrator would set up backups in a tape-based environment.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

In tape-based backup, administrators can structure backups for one client to many different tape drives at the same time (multi-streaming) so the backup would complete as soon as possible. Multiplexing is the process of alternately sending (interleaving) data from multiple clients to a single tape.

[ How is your data center holding up? Read State Of Data Centers: Hot, Crowded, Virtual. ]

In addition to allowing a customer to optimally deduplicate multi-streamed, multiplexed database backups, DeltaStor 6.1 now also includes the ability to detect changes to data in sub-8 KB blocks of data (8 KB is the default for Oracle databases) with no effect on the performance of the system.

Using byte-level differential deduplication, the backup process can detect changes to metadata or tags that the Oracle database changes when it writes a block and is able to deduplicate the rest of the data in the sub-8 KB block leading to high deduplication ratios. This sub-8 KB capability is an important differentiation between Sepaton's DeltaStor technology and the hash-based algorithms other vendors use. When hash-based deduplication appliances attempt to hash small sub-8 KB blocks to get better deduplication ratios, the hash table grows out of memory and ingest performance slows down and the database backup no longer fits in the backup window and the backup fails.

DeltaStor 6.1 also offers support for Auto Image Replication (A.I.R.), Optimized Synthetics, Granular Recovery of Exchange mailboxes, and NetBackup Accelerator, as well as support for AIX and SUSE Linux Enterprise Server x86-64.

Symantec OST A.I.R. provides for the automated replication between NetBackup domains. With Optimized Synthetics, the Sepaton platform can create full backups from previous backups and incremental backups at any time. The customer will perform one full backup and then perform incremental backups after that. This capability minimizes backup times, disk utilization, simplifies restores, and improves the likelihood of successful recoveries.

In addition, Sepaton now supports more granular recovery of Exchange mailboxes and Active Directory entries.

Finally, Sepaton supports and is certified for NetBackup Accelerator, a client-side data reduction feature introduced with NetBackup 7.5. NetBackup Accelerator only transmits the changed blocks in files, allowing reduced network traffic between the client and the media server and between the media server and the Sepaton backup appliance.

Deni Connor is founding analyst for Storage Strategies NOW, an industry analyst firm that focuses on storage, virtualization, and servers.

From thin provisioning to replication to federation, virtualization options let you reclaim idle disks, speed recovery, and avoid lock-in. Get the new, all-digital Storage Virtualization Guide issue of Network Computing. (Free registration required.)



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.