A School of Computer Science grad student's dissertation has been transformed into a service aimed at improving the databases that power popular websites.
OtterTune, a play on the once ubiquitous Auto-Tune, uses machine learning to automatically optimize databases, improving performance and efficiency and potentially saving companies time and money. Users could see faster loading times and improved services with a database humming along in the background.
"There are hundreds of settings to consider when optimizing a database, too many for humans to properly tune," said Dana Van Aken, one of the company's co-founders. "OtterTune takes human trial and error out of the mix."
The company is based on Van Aken's dissertation. She founded the company with her advisor, Andy Pavlo, an associate professor in the Computer Science Department; and Bohan Zhang, who earned his master of computational data science from CMU and worked with Van Aken and Pavlo as a research assistant.
The company announced a commercial version of its service Wednesday and $2.5 million in seed funding, led by venture capital firm Accel. OtterTune is based in Pittsburgh and full of Carnegie Mellon talent. Seven of its 12 employees are either CMU faculty or alumni.
"Database management systems now exceed the administrator's ability to optimize them," said Pavlo, the CEO of OtterTune. "We've put years of research into solving this problem, which we know will lead to significant increases in efficiencies and cost savings for customers."
Don't let the company's playful name or DJing otters wearing headphones fool you. It is serious about tuning a database for optimal performance. In case studies, the OtterTune improved efficiency by 33% to 50%, cut one company's costs in half, and saved another tens of thousands of dollars.
"It turns out, otters are actually vicious animals," Pavlo said.