![]() The reverse is also true: a standard table cannot be converted into a virtual table. Once created, a virtual table cannot be changed to be a standard (non-virtual) table.A virtual table cannot represent an activity and do not support business process flows.Offline caching of values is not supported for virtual tables.Virtual tables cannot be enabled for queues.Charts and dashboards are not supported for virtual tables.Search functionality is not supported for virtual tables as they do not persist data.Although you can add virtual table columns as a lookup on a grid or other UI views, you cannot filter or sort based on this virtual table lookup column.Any desired calculations must be done on the external side, possibly within or directed by the data provider. A column on a virtual table cannot be calculated or rollup.You must be able to model any table relationships in Dataverse.You can use simple types representing text, numbers, choices, dates, images, and lookups. All table properties must be represented as Dataverse table columns.All tables in the external data source must have an associated GUID primary key.It must be possible to model the external data as a Dataverse table.Access to the virtual table data can be turned on or off for individual users based on their security role. The security filtering applied to user-owned tables is not supported. ![]() Only organization-owned tables are supported.Limitations of virtual tablesįollowing are the limitations in virtual tables that must be considered. In this example, a corresponding virtual table data source would also be provided to supply user and connection information for the external database. The most direct way to achieve this is to actually use GUIDs as primary keys in the external data source. (Note that these external data names are often different than their corresponding virtual table names.) A specific, required mapping occurs for the entity ID field: the data provider must be able to provide this GUID and associate it to the external record that represents this record. For example, a virtual table might be represented as a row in an external relational database, and each of its columns might correspond to a column in that row. The custom table type and its columns must be mapped to the corresponding data in the external data source. However, additionally, you then connect the virtual table to a data provider to manage data operations. Initially, defining a virtual table is the same as defining a custom table: you specify the table, columns, and relationships for the new virtual table type. Developers can implement plug-ins and register them using the Plug-in Registration tool for each of the CRUD operation supporting the virtual table. Full CRUD operation is now supported for custom virtual table data provider. If a data provider cannot be found for your external data source, you can develop a custom virtual table data provider for more information, see Virtual table data providers. An Azure Cosmos DB (formerly Microsoft Document DB) provider is available from AppSource.This provider supports create, read (retrieve, retrieve multiple), update and delete operations. An OData v4 provider is included with the service and is installed by default. ![]() The following data providers ship with Dataverse: Each virtual table type is associated with a virtual table data provider and (optionally) some configuration information from an associated virtual table data source. Instead during runtime, when a record is required, its state is dynamically retrieved from the associated external system. Virtual tables, data providers and data sourcesĪ virtual table is a definition of a table in the Dataverse platform without the associated physical tables for records created in the Dataverse database. For more information about managing virtual tables from the user interface, see Create and edit virtual tables that contain data from an external data source. ![]() This section discusses the implications of virtual tables for developers.
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