The default configuration in most databases is meant for broad compatibility rather than performance. Database tuning is a process in which the configurations of a database are modified to achieve optimal performance. Databases have hundreds of configuration knobs that control various factors, such as the amount of memory to use for caches or how often the data is written to the storage.

The problem with these knobs is that

they are not standardized (i.e., two databases may have a different name for the same knob),
not independent (i.e., changing one knob can impact others),
and not universal (i.e., what works for one application may be suboptimal for another).

In reality, information about the effects of the knobs typically comes only from (expensive) experience.

OtterTune is automatic database tuning software that promises to overcome these problems. It uses machine learning to tune the configuration knobs of your database automatically to improve performance.

In this episode, we interview Andy Pavlo. Andy is a Database Professor at Carnegie Mellon and Co-Founder of OtterTune.

Sponsorship inquiries: sponsor@softwareengineeringdaily.com

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