If there’s one big question about Qubole, though, it has to be the emergence of a rather-large SQL-on-Hadoop market since the company launched. Although Hive has been an important part of the Hadoop stack over the past few years, its MapReduce foundation is beginning to show its age in terms of query speed, and the new breed of database startups pushing SQL analytics atop Hadoop are quick to point this out.
Thusoo has certainly noticed this activity, but he stills sees Qubole as being in a good position. For starters, he said, the company is looking at interactive analytics projects such as Impala and Shark to see how they might integrate with the Qubole platform, and Hadoop startup Hortonworks is leading the Stinger project to drastically boost the speed of Hive itself.
Further, there’s the fact that Qubole itself has already optimized its platform to run, on average, about five times faster than Hive would normally run on Amazon Elastic MapReduce alone.
“We’re also keeping a close tab on other projects in our space,” Thusoo said. “We have a lot of options … to play with.”