Dell Products Inc.

Lokesh Dasam

Dhilip S Kumar

Techniques are disclosed for enabling a multi-model and clustering database system. For example, a query from a client is received at a primary cluster in a clustering database system implemented over one or more processing platforms. The primary cluster analyzes the query to determine an intent of the query and, based on the intent of the query, to identify at least one secondary cluster from a plurality of secondary clusters in the clustering database system to execute the query. The primary cluster manages the plurality of secondary clusters, and one or more of the plurality of secondary clusters support a data model type that is different than a data model type of one or more others of the plurality of secondary clusters.

Multi-model and clustering database system

A method comprises reading data from a source database, identifying one or more data types corresponding to the source database, identifying a destination database for the data, and identifying one or more data types corresponding to the destination database. In the method, a destination database model to use in connection with writing the data in the destination database is generated. The generation of the destination database model is based at least in part on the one or more data types corresponding to the destination database, and is performed using one or more machine learning algorithms.

Database gateway with machine learning model

A Database Query Time Estimator (DQTE) module as a run-time tool to estimate and display the total time to complete a database query while the query is executing. The DQTE module invokes a runtime algorithm to compute the set of rows or blocks in a database that will be resulted at each step of a query's execution plan. The DQTE module may optimize the current execution plan to create one or more parent-child processes and may assign tasks to these processes to monitor the progress of each step in the execution plan. The progress of the child processes is then rolled up to the root parent level to come up with a time value, which is the Estimated Time of Arrival (ETA) to complete the whole execution of the query. The DQTE module may read only the header information of the database objects for a complete snapshot of the object.

Growing community of inventors

Khammam, India

Lokesh Dasam