Researchers tout vector-based automated tuning in PostgreSQL • The Register

Automated database systems based on vector embedding algorithms could improve the performance of default settings on common PostgreSQL database services by a factor of two to ten, according to a database researcher.

Speaking to The Register , Andy Pavlo, associate professor at Carnegie Mellon University Database Group, explained that the problem of automating the options for database tuning and optimization – a long cherished skill of DBAs – related to the fact that it was difficult for a single model to get to grips with all the parameters in one go.

While experienced DBAs might have the experience to tune system performance, developers building modern systems tend to call on a database service from a popular hyperscaler – AWS's relational database service (RDS), for example – and are l