World-class data management and storage solutions in the biggest public clouds.Visit Cloud Services
Our industry-leading solutions are built so you can protect and secure your sensitive company data.Visit Cyber Resilience
This research seeks to provide sufficient hints from the database storage engine to the underlying storage system to allow it more efficient data management and I/O operations when accessing data when executing queries. With OLTP workloads, the idea is to automatically partition the data according to continuous monitoring and observations what tuples are accessed (read or updated) together. Similarly, for OLAP workloads, the DB storage engine will monitor what columns of data are accessed together and provide hints to the storage system so that it can collocate, distribute and/or partition the data as necessary.