Big Data. Big Decisions
InformationWeek
Special Coverage Series


Carfax Selects MongoDB To Drive 11 Billion Records

Vehicle-history service switches to open source, NoSQL database with an eye to exploring its massive data set in new ways.

There's a 30-year-old relational database up on blocks at Carfax's Columbia, Mo., office.

On Tuesday, the Web service, which supplies used-vehicle history reports to millions of consumers and 30,000 dealerships every year, announced plans to retire its VMS-based RDBMS and switch to MongoDB, the open source, document-oriented database developed and supported by 10gen.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

"VMS has been a very valuable OS for us," Carfax CTO Joedy Lenz told InformationWeek in a phone interview. "Unfortunately, with our data volumes, it became fairly expensive to operate and maintain." The production VMS system will be retired within 12 months, he said.

Carfax's Vehicle History Report, created in 1986, is the largest vehicle-history database ever assembled, with nearly 11.5 billion records and growing at 1 billion new records a year. It comprises information from more than 75,000 sources, such as U.S. and Canadian motor vehicle departments, service and repair facilities, insurance companies, and police departments.

[ For more on database vendors, see InformationWeek's Big Data 101: New Vendor-Neutral Guide. ]

When it takes over the driver's seat, the MongoDB will run across 50 servers. Lenz declined to name the hardware vendor. But 10gen CEO Max Schireson told InformationWeek on the phone: "Using inexpensive commodity servers means they can scale out," Schireson said.

While an open source product, 10gen claims some 500 customers worldwide who pay for its consulting and services. This customer list includes marquee Web brands like eBay and Craigslist, but traditional businesses as well, including three of the top 10 global banks and telcos, among others.

Another advantage of using MongoDB is its built-in redundancy. If a node fails, work is picked up by one or more secondary nodes.

In fact, Carfax already uses a seven-node VMS system. However, Lenz shared that in early performance testing, MongoDB ran transactions up to four times faster. But speed and cost savings weren't the only reasons Carfax decided to migrate to a NoSQL architecture.

Unlike their relational predecessors, NoSQL databases like MongoDB, Cassandra and Riak use a flexible, schema-less design that is especially well suited for massive amounts of variable data.

"Mongo does [transaction processing] with the added benefit of analytics and data mining," he said. "The sky's the limit ... we're just scratching surface."

As NoSQL products like MongoDB win new adherents, relational database vendors haven't been sitting still. Just last month, Oracle announced a major upgrade, MySQL 5.6, which includes features for high-scale deployments. For example, Oracle announced it would support direct access to data through the Memcached API, which is up to nine times faster than accessing data through SQL parsing.



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.