No matter what anyone tells you, getting started with Big Data isn’t easy.

There are the ever-growing three V’s (Volume, Velocity and Variability) of data to contend with; new style databases that most of us are virgin to; hardware, operating systems and software that need to be purchased, installed, configured and tuned, and all of the trial and error that’s inherent in working with anything new, let alone, humongous. Never mind any anticipated, or unanticipated, needs for agility and scaling …

Hardly anyone gets it right the first time, on time, for any length of time, unless they’re set up to win from the start.

Built for Success

Open Source MongoDB sponsor, 10gen, and global cloud infrastructure provider SoftLayer Technologies understand all of this only too well; that’s why they’ve partnered to deliver MongoDB on-demand. It’s a first of its kind Cloud offering that takes the guesswork out of deploying and managing MongoDB production class systems.

“We help our customers get it exactly right from the start,” says Duke Skarda, chief technology officer of SoftLayer Technologies.

The two companies have worked closely together to engineer optimized hardware and OS configurations, to automate the deployment of multi-data center clusters, and to provide integrated monitoring and support. The resulting SoftLayer MongoDB systems offer a complete solution set through SoftLayer’s portal or API for ease of management, administration and maintenance.

The cloud solution “shortens time to market and accelerates time to launch,” says Jared Rosoff, director of product marketing and technical alliances for 10gen.

SoftLayer’s MongoDB service is sold on a pay-as-you-go basis, which makes it highly attractive for customers who have projects that need to start fast, allow for agility and scaling, and run for fixed periods of time.

Under 10gen’s traditional, annual subscription model, the responsibility for hardware and operating systems belongs to the client which means that both the in-house infrastructure and pool of in-house talent might likely need to be ramped-up and retrained.