OtterTune Launches to Improve Database Performance through Automated Database Configuration Tuning
Receives $2.5 million in seed funding, led by Accel
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OtterTune today announced the private beta of the new OtterTune automatic database tuning service. The system uses machine learning (ML) to automatically generate configuration settings to improve database performance and efficiency. The company also announced that it has received an initial seed funding round, led by
OtterTune machine learning algorithms at work tuning a database, more than doubling its throughput.
As companies look to manage their database costs and performance in the cloud or on-premises, significant benefits can be realized by tuning configuration settings. However, with hundreds of settings to consider, most database administrators must rely on time-consuming trial and error tuning or boilerplate configuration settings that can leave databases well short of optimal performance. As a result, it is estimated that 40% of cloud databases are over-provisioned, resulting in hundreds of millions of dollars in wasted IT infrastructure spending industry-wide per year.