Big Data. Big Decisions
InformationWeek
Special Coverage Series


Amazon Launches Big Data Service

DynamoDB cloud service, based on Amazon's own big data handling experience, offers NoSQL database capabilities and storage built for speed.

12 Top Big Data Analytics Players
12 Top Big Data Analytics Players
(click image for larger view and for slideshow)
Amazon Web Services on Wednesday added a beta service, DynamoDB, to its cloud service offerings as a way to bring a big-data, NoSQL system to its customers.

"You can dial up database capacity without thinking about it," said Werner Vogels, CTO of AWS, in a 9 a.m. webcast today. "It's not database software. It's a database service," one that can perform "consistently fast," he said.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

Anyone creating an account for the service can establish a database table with the data stored on solid-state disks (SSDs). That gives the service a high degree of performance predictability by eliminating calls to rotating disks. "Customers can typically achieve average service-side in the single-digit milliseconds," Vogels wrote in an early morning post to his All Things Distributed blog.

The data is spread across multiple availability zones, or data center units with independent networking and power supplies.

[ Big-data handling is a necessary part of the data center. Read more at Three BI Trends Every CIO Must Understand. ]

The customer tells DynamoDB through the AWS management console how many requests it will see per second, then AWS spreads the database table across a sufficient number of servers to provide it, Vogels said during the webcast. If unexpected traffic appears, the customer may dial up more requested capacity at the console.

One beta customer requested 250,000 writes to the system per second, and used it over a three-day period. "It was great testimony to our scalability and throughput," Vogels said.

DynamoDB will give customers the ability to make a performance-vs.-consistency tradeoff. Customers automatically will get high performance with "eventual" consistency, or relational database type of assurance of the same answer to the same question all the time. Eventual consistency is often used in situations in which the precision of the answer is less important than the speed of response. For instance, a game player, asking how many fellow players are available, might be satisfied by with an answer that is off by a few players, even if a precise answer were available several seconds later.

DynamoDB is added to Amazon's SimpleDB database service and its Relational Database Service. It has been integrated with another existing service, Elastic Map Reduce, AWS's implementation of the Hadoop big data distribution and sorting system.

Dynamo was the name Amazon engineers gave to an early NoSQL system they built to cope with the fluctuation in holiday shopping traffic. The installed commercial relational database system was proving inadequate to the scale of the task.

Dynamo, along with Google's BigTable, became the prototype for a number of followup NoSQL systems, including Cassandra and Riak. "A number of outages at the height of the 2004 holiday shopping season can be traced back to scaling commercial technologies (on Amazon's e-commerce systems) beyond their boundaries," wrote Vogels in his blog. Big data handling had been born, and now DynamoDB combines features of relational database and NoSQL technologies in a cloud service.

More than 700 IT pros gave us an earful on database licensing, performance, NoSQL, and more. That story and more--including a look at transitioning to Win 8--in the new all-digital Database Discontent issue of InformationWeek. (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.