Data-source overview

In Microsoft Power Apps, you use data sources to connect to and store your data. You can access data within the Office 365 ecosystem in locations such as Common Data Service, SharePoint, SQL Server, and other on-premises sources; Azure or other cloud services; a web API; or any of more than 200 built-in connectors.

This graphic shows the most common data sources.

Data sources

The Power Apps Per app plan or Power Apps Per user plan provides access to premium connectors, such as these examples:

  • Common Data Service (database)

  • SQL Server

  • Salesforce

  • DocuSign

  • MailChimp

  • Oracle

  • ServiceNow

  • Workday HCM

Tabular or action-based data sources

Data sources provide data as either actions or one or more tables. Some data sources, such as Common Data Service, SharePoint, and SQL Server provide your data in a structured table. With table data sources, you can easily display the data in a gallery or a form. In Power Apps, you can use multiple functions for working with tables of data.

Other data sources, such as the Office 365 Users connector or Project Online, are action-based. When you connect to these data sources, you can run different actions by using various functions. Generally, you must explicitly connect these functions to controls to interact with them. They do not work automatically like tabular data sources. For example, this function queries data.

Office365Users.SearchUser()

In contrast, this function updates data.

Office365Users.UpdateMyProfile({aboutMe:"I love Power Apps"})

Custom connectors

You can create a custom connector to query any web API if no built-in connector suits your needs. You don't need to write C# code to create a custom connector. You can create your connector with just a few steps by using a Postman or OpenAPI file. For more information, see Custom connectors for canvas apps. The remainder of this learning path discusses how to add a data source, display data in a gallery, build data sources by using collections, and work with large data sets efficiently by understanding delegation.