Big Data. Big Decisions
InformationWeek
Special Coverage Series


Gartner Ranks Data Warehousing Leaders

Magic Quadrant puts Teradata in the top spot with Oracle and IBM close behind. Report sees growing interest in column-store, in-memory and cloud-based technologies.

Demand for data warehousing (DW) technologies held steady in 2010 even as many other IT categories retrenched in a tough economy. That's the macro take detailed in Gartner's just-released "Magic Quadrant for Data Warehouse Data Management Systems."

Despite steady demand, the DW market is far from static. Three key players, Greenplum, Netezza and Sybase, where acquired in 2010, and the consolidation is likely to continue, says Gartner. What's more, column-store, in-memory and cloud-based databases may have a disruptive impact on the market.

What has been stable has been the top three spots in Gartner's Magic Quadrant (MQ). Teradata is once again in the top-right position, highest on the vertical "ability-to-execute" axis and farthest right on the horizontal "completeness of vision" axis. It's followed by Oracle and IBM, which have been in the number-two and number-three spots for years.

The MQ details "strengths" and "cautions" on every vendor included in the report. Teradata's strengths include its flexible systems management software and its mature capability to integrate advanced analytics, says Gartner.

Teradata has positioned its 2650 appliance against competitors IBM Netezza and Oracle Exadata, but Gartner cautions that customers aren't quite clear on when to choose the appliance over Teradata's enterprise-class platform. What's more, the appliance doesn't always stand out in performance when tests and planned uses don't involve highly mixed workloads -- long a strong suit for Teradata.

Oracle strengths include its commanding (48%) share of the relational database market and its Oracle RAC (Real Application Clusters) technology. Gartner says RAC ensures high availability while also serving as the foundation for scaling out the Exadata Database Machine. Oracle eased administration with its 11g database upgrade through improved materialized view and cube management and an added Partition Advisor that suggests best configurations to maximize performance.

Gartner described the 11g upgrades as strengths, yet it also cautions that many customers say Oracle database administrative demands are higher than some competitive products. Another Oracle caution: Watch out for contract and pricing practices including "high prices, uneven and wide-ranging discounts, increasing software audits, high cost of maintenance and reluctance to negotiate on renewals," according to the report.

IBM's DB2-based products and acquired Netezza products are covered separately in the MQ report (with the former ranked third on the quadrant). IBM is the only database vendor that can offer an information architecture spanning all systems, Gartner notes. That includes OLTP, DW and retirement of data (the last covered by Optim products). IBM has also embraced Hadoop through InfoSphere BigInsights, which Gartner says gives DW managers confidence that IBM products are evolving to meet new demands.

The key caution on IBM's DB2 portfolio? There don't seem to be enough architects and DBAs to go around. This seems to be confirmed by the fact that IBM has been more selective about the projects it goes after. Not counting Netezza, IBM's market share declined about 0.7% while Oracle's declined about 1.8% in 2010, Gartner reports.

The three other vendors in the MQ top-right leaders quadrant are the three key vendors acquired in 2010: Sybase (by SAP), Netezza (by IBM) and Greenplum (by EMC). Sybase is a bit more of a visionary, as positioned by Gartner, while the last two are in fairly equal position.

 1 | 23  | Next Page »


Related Reading


More Insights




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.