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How big data is changing the database landscape for good

Katherine Noyes | Nov. 11, 2015
From NoSQL to NewSQL to 'data algebra' and beyond, the innovations are coming fast and furious

Workloads, meanwhile, have also changed. Whereas 10 years ago websites were largely static, for example, today we have live Web service environments and interactive shopping experiences. That, in turn, demands new levels of scalability, he said.

Companies are using data in new ways as well. Whereas traditionally most of our focus was on processing transactions -- recording how much we sold, for instance, and storing that data in place where it could be analyzed -- today we're doing more.

Application state management is one example.

Say you're playing an online game. The technology must record each session you have with the system and connect them together to present a continuous experience, even if you switch devices or the various moves you make are processed by different servers, Olofson explained.

That data must be made persistent so that companies can analyze questions such as "why no one ever crosses the crystal room," for example. In an online shopping context, a counterpart might be why more people aren't buying a particular brand of shoe after they click on the color choices.

"Before, we weren't trying to solve those problems, or -- if we were -- we were trying to squeeze them into a box that didn't quite fit," Olofson said.

Hadoop is a heavyweight among today's new contenders. Though it's not a database per se, it's grown to fill a key role for companies tackling big data. Essentially, Hadoop is a data-centric platform for running highly parallelized applications, and it's very scalable.

By allowing companies to scale "out" in distributed fashion rather than scaling "up" via additional expensive servers, "it makes it possible to very cheaply put together a large data collection and then see what you've got," Olofson said.

Among other new RDBMS alternatives are the NoSQL family of offerings, including MongoDB -- currently the fourth most popular database management system, according to DB-Engines -- and MarkLogic.

"Relational has been a great technology for 30 years, but it was built in a different era with different technological constraints and different market needs," said Joe Pasqua, MarkLogic's executive vice president for products.

Big data is not homogeneous, he said, yet in many traditional technologies, that's still a fundamental requirement.

"Imagine the only program you had on your laptop was Excel," Pasqua said. "Imagine you want to keep track of network of friends -- or you're writing a contract. Those don't fit into rows and columns."

Combining data sets can be particularly tricky.

"Relational says that before you bring all these data sets together, you have to decide how you're going to line up all the columns," he added. "We can take in any format or structure and start using it immediately."

 

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