Cloudant databases vary from a gigabyte all the way to 100TB, he said. Customers are running applications for advertising analytics, "datamart-type applications," and "understanding the connections in a social graph -- not in an [extract, transform and load] workflow kind of way using Hadoop, but in real time," he said.

While cloud databases can solve scaling problems, they also present new challenges, the panelists acknowledged. The quality of server hardware in the public cloud is "often a notch down," said Zane, so companies for whom high-speed analytics are critical may still want to buy and manage their own hardware, he said.

And while many service providers claim to be "cloud agnostic," the reality is often different, Miller said. Cloud software vendors need to do "a lot of reverse engineering" to figure out what the architectures at services like Amazon EC2 look like "behind the curtain," in order to get maximum performance from their database software.

Still, Sharir and Zane were both optimistic that "big data analytics" would be the"killer application" for their products. For Starkey it is simply "the Web."

"Everyone on the Web has the same problem, this very thin pipe trying to get into database systems," he said. "Databases don't scale, and it shows up in a thousand places."