Abstract: A multi-table data validation tool is run following migration of data from a source database to a target database. The multi-table data validation tool extracts data from source and target locations into memory, transforms data and masks confidential data as needed, then performs two types of data comparison, including row count and data content comparison. Result files of each comparison are available to the migration team, enabling updates and improvements to the migration tools. The multi-table data validation tool may further be used to extract requested data from either the source database or the target database. The multi-table data validation tool may be dockerized as a container for ease of deployment in different environments.

Abstract: A multi-table data validation tool is run following migration of data from a source database to a target database. The multi-table data validation tool extracts data from source and target locations into memory, transforms data and masks confidential data as needed, then performs two types of data comparison, including row count and data content comparison. Result files of each comparison are available to the migration team, enabling updates and improvements to the migration tools. The multi-table data validation tool may further be used to extract requested data from either the source database or the target database. The multi-table data validation tool may be dockerized as a container for ease of deployment in different environments.

Abstract: A multi-table data validation tool is run following migration of data from a source database to a target database. The multi-table data validation tool extracts data from source and target locations into memory, transforms data and masks confidential data as needed, then performs two types of data comparison, including row count and data content comparison. Result files of each comparison are available to the migration team, enabling updates and improvements to the migration tools. The multi-table data validation tool may further be used to extract requested data from either the source database or the target database. The multi-table data validation tool may be dockerized as a container for ease of deployment in different environments.

Abstract: The present disclosure relates to systems and methods for updating virtual machines without rebuilding distributed databases thereon. In one example, a system for updating a virtual machine on a cloud service may include at least one processor configured to: generate and transmit, to the cloud service, a first command to disconnect a virtual storage from a first virtual machine; after the virtual storage is disconnected, generate and transmit, to the cloud service, a second command to offline the first virtual machine; generate and transmit, to the cloud service, a third command to build a second virtual machine; after the second virtual machine is built, generate and transmit, to the cloud service, a fourth command to connect the virtual storage to the second virtual machine; and generate and transmit, to the cloud service, a fifth command to online the second virtual machine with the address of the virtual machine.

Abstract: The present disclosure relates to systems and methods for updating virtual machines without rebuilding distributed databases thereon. In one example, a system for updating a virtual machine on a cloud service may include at least one processor configured to: generate and transmit, to the cloud service, a first command to disconnect a virtual storage from a first virtual machine; after the virtual storage is disconnected, generate and transmit, to the cloud service, a second command to offline the first virtual machine; generate and transmit, to the cloud service, a third command to build a second virtual machine; after the second virtual machine is built, generate and transmit, to the cloud service, a fourth command to connect the virtual storage to the second virtual machine; and generate and transmit, to the cloud service, a fifth command to online the second virtual machine with the address of the virtual machine.

Abstract: The present disclosure relates to systems and methods for updating virtual machines without rebuilding distributed databases thereon. In one example, a system for updating a virtual machine on a cloud service may include at least one processor configured to: generate and transmit, to the cloud service, a first command to disconnect a virtual storage from a first virtual machine; after the virtual storage is disconnected, generate and transmit, to the cloud service, a second command to offline the first virtual machine; generate and transmit, to the cloud service, a third command to build a second virtual machine; after the second virtual machine is built, generate and transmit, to the cloud service, a fourth command to connect the virtual storage to the second virtual machine; and generate and transmit, to the cloud service, a fifth command to online the second virtual machine with the address of the virtual machine.