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In mixing big data and the cloud, architectural issues loom large

Deploying cloud databases might be relatively easy, but designing an effective cloud-based big data architecture isn't so simple, says consultant David Linthicum.

Moving big data systems to the cloud can be easy in some ways and difficult in others, according to David Linthicum, a senior vice president at consulting company Cloud Technology Partners in Boston. On the plus side, he said, new systems can be deployed almost instantly, and cloud data management platforms have matured to the point where issues such as data security are well taken care of.

"Deploying cloud databases is simple," Linthicum said. "You don't have to buy 20 servers and bolt them onto a rack, get the database software integrated or get the engineers in there because things just aren’t working right." Instead, you call up a cloud provider, and it does the provisioning for you.

But he added that creating an architecture combining big data and the cloud can be a challenge, particularly if a company -- no matter the size -- doesn't adopt a service-based approach for dealing with data. And incorporating a data services layer into a big data architectural framework is something that many organizations eyeing the cloud don't think about ahead of time, he said.

In addition, many existing systems need to be re-architected to take part in the cloud movement, Linthicum said. That's another reason why companies with a blank IT slate may be at an advantage when it comes to moving big data applications into the cloud -- and why doing so is often a more appealing option for them than it is for more established organizations.

Jack Vaughan is SearchDataManagement's news and site editor. Email him at, and follow us on Twitter: @sDataManagement.

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