NoSQL databases don't use a relational data model, and they typically have no SQL interface. Whereas many NoSQL stores compromise consistency in favor of speed and other factors, MarkLogic pitches its own offering as a more consistency-minded option tailored for enterprises.
There's considerable growth in store for the NoSQL market, according to Market Research Media, but not everyone thinks it's the right approach -- at least, not in all cases.
NoSQL systems "solved many problems with their scale-out architecture, but they threw out SQL," said Monte Zweben, Splice Machine's CEO. That, in turn, poses a problem for existing code.
"Our philosophy is to keep the SQL but add the scale-out architecture," Zweben said. "It's time for something new, but we're trying to make it so people don't have to rewrite their stuff."
Deep Information Sciences has also chosen to stick with SQL, but it takes yet another approach.
The company's DeepSQL database uses the same application programming interface (API) and relational model as MySQL, meaning that no application changes are required in order to use it. But it addresses data in a different way, using machine learning.
DeepSQL can automatically adapt for physical, virtual or cloud hosts using any workload combination, the company says, thereby eliminating the need for manual database optimization.
Among the results are greatly increased performance as well as the ability to scale "into the hundreds of billions of rows," said Chad Jones, the company's chief strategy officer.
An altogether different approach comes from Algebraix Data, which says it has developed the first truly mathematical foundation for data.
Whereas computer hardware is modeled mathematically before it's built, that's not the case with software, said Algebraix CEO Charles Silver.
"Software, and especially data, has never been built on a mathematical foundation," he said. "Software has largely been a matter of linguistics."
Following five years of R&D, Algebraix has created what it calls an "algebra of data" that taps mathematical set theory for "a universal language of data," Silver said.
"The dirty little secret of big data is that data still sits in little silos that don't mesh with other data," Silver explained. "We've proven it can all be represented mathematically, so it all integrates."
Equipped with a platform built on that foundation, Algebraix now offers companies business analytics as a service. Improved performance, capacity and speed are all among the benefits Algebraix promises.
Time will tell which new contenders succeed and which do not, but in the meantime, longtime leaders such as Oracle aren't exactly standing still.
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