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OtterTune to compete with Oracle automation, but also for open source databases Lindsay Clark Fri 14 May 2021 // 10:45 UTC Share Copy A university spin-out startup has announced a private beta of an automated database tuning service which its founder claims can double the performance or halve the cost of the popular AWS Relational Database Service. Among its marketing hype, though, is the, erm, novel approach of launching a hip-hop album of beats and screeching otters. More of that later. Originating from a project at Carnegie Mellon Database Group, OtterTune is based on the idea you can use machine learning to identify the optimal setting for database parameter knobs, a task well beyond most developers and something even seasoned DBAs struggle with, given the number of databases on the market that they might be required to manage. ....
OtterTune Launches to Improve Database Performance through Automated Database Configuration Tuning Receives $2.5 million in seed funding, led by Accel News provided by Share this article 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 sh ....