Abstract: Methods, apparatus, and processor-readable storage media for automatically detecting data offloading methods using data bucketing and machine learning techniques are provided herein. An example computer-implemented method includes obtaining operations data and configuration data for one or more storage objects in a database; determining one or more times at which data offloading is to be carried out for at least one of the storage objects in the database, wherein determining the one or more times includes processing at least a portion of the operations data using one or more machine learning techniques; generating at least one data offloading protocol, comprising one or more data offloading methods, by processing at least a portion of the configuration data; and automatically executing, in accordance with the one or more determined times, the at least one generated data offloading protocol for at least a portion of the one or more storage objects in the database.

Abstract: Methods, apparatus, and processor-readable storage media for predicting statistics gathering times for database activity data using machine learning techniques are provided herein. An example computer-implemented method includes obtaining activity data pertaining to at least one storage object of a given database; determining one or more times to gather statistics related to activity data pertaining to the at least one storage object of the given database by processing at least a portion of the obtained activity data using one or more machine learning techniques; and performing at least one automated action related to statistics gathering based at least in part on the one or more determined times.

Abstract: Methods, apparatus, and processor-readable storage media for automatically detecting data offloading methods using data bucketing and machine learning techniques are provided herein. An example computer-implemented method includes obtaining operations data and configuration data for one or more storage objects in a database; determining one or more times at which data offloading is to be carried out for at least one of the storage objects in the database, wherein determining the one or more times includes processing at least a portion of the operations data using one or more machine learning techniques; generating at least one data offloading protocol, comprising one or more data offloading methods, by processing at least a portion of the configuration data; and automatically executing, in accordance with the one or more determined times, the at least one generated data offloading protocol for at least a portion of the one or more storage objects in the database.

Abstract: Methods, apparatus, and processor-readable storage media for predicting statistics gathering times for database activity data using machine learning techniques are provided herein. An example computer-implemented method includes obtaining activity data pertaining to at least one storage object of a given database; determining one or more times to gather statistics related to activity data pertaining to the at least one storage object of the given database by processing at least a portion of the obtained activity data using one or more machine learning techniques; and performing at least one automated action related to statistics gathering based at least in part on the one or more determined times.

Abstract: A method includes obtaining a relational model, the relational model comprising a plurality of nodes and a plurality of links, each of the links of the plurality of links connecting one or more nodes of the plurality of nodes, and each link corresponding to a relationship between a first node and a second node, receiving a request to update the relational model, the request comprising information corresponding to an added and/or edited first node, determining a first probability that the first node is in a relationship with a second node and a second probability that the first node is in a relationship with a third node, and updating the relational model to include the relationship between the first node and the second node at the first probability and the relationship between the first node and the third node at the second probability.