"If your app is running on Amazon East or Amazon Europe, you'd better be close to where we're at. The payload [the data] needs to be in the same place" as the application, he said.

Unlike Xeround, ParAccel's software is designed to run analytics workloads, and the sweet spot for its distributed database system is "around the 25TB range," said CTO Barry Zane.

"We're the epitome of big data," he said. ParAccel's customers are businesses that rely on analyzing large amounts of data, including financial services, retail and online advertising companies.

One customer, interclick, uses ParAccel to analyze demographic and click-through data to let online advertising firms know which ads to display to end users, he said. It has to work in near real-time, so interclick runs an in-memory database of about 2TB on a 32-node cluster, Zane said. Other customers with larger data sets use a disk-based architecture.

ParAccel also lets developers write SQL queries, but with extensions so they can use the MapReduce framework for big-data analytics.