Vmware, Inc.

Sangeeta Soman

Joshua Glenn Broch

Abhishek Mishra

Zundra Vennaldo Daniel

Manu Nazareth

Liny Chandran

Adam Michael Hardy

Aashima Madaan

Sriram Devalapalli

Trigger based analytics database synchronization is described. In one example case, a trigger is invoked based on an operation issued for a record in a transactional database. According to the trigger, one or more data values for synchronization from the transactional database to an analytics database are determined. A message including the data values is formed and added to a message queue through a message infrastructure service including a message broker. In turn, the values from the message are stored in a suitable memory space, such as a staging table, for forwarding to an analytics computing system. Using the trigger and the message infrastructure service, execution of the transactional database operation can be detached in execution from the addition of the value to the staging table and synchronization with the analytics computing system.

Trigger based analytics database synchronization

Various examples for performing rule processing for device management data evaluation are described. According to some examples, one or more computing devices can receive new device data from a client device indicative of a current configuration of the client device and identify a change of a device configuration value from a past device configuration value by comparing the new device data to historic device data. The computing devices can send the new device data to a rule evaluation service to identify one or more rules associated with the device configuration value a rule action service to perform an action specified in the rules. The rule action service can determine the action to perform based on the device configuration value.

Efficient rule processing for device management data evaluation

Event based analytics database synchronization is described. In one example, an event tracking engine can sequence through batches of records in a transactional database that is being synchronized to an analytics database. The event tracking engine can determine a last version attribute associated with the batch, and query the transactional database to identify any records for the batch having a more recent version attribute than the last version attribute. When any records in the transactional database having a more recent version attribute are identified, the event tracking engine finds the data values in the record are different than those in the analytics database. The data values can be normalized, for example, before being forwarded to an analytics system for incorporation into the a analytics database. Over time, changes in the transactional database are identified and populated or mirrored in the analytics database.

Event based analytics database synchronization

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Bengaluru, India

Sangeeta Soman