Data Sources
The Curity Identity Server uses one or more Data Sources as an abstration that represents a backend system that stores and provides data.
Use Cases#
The Curity Identity Server uses both permanent and temporary identity data. During user authentication and token issuance the system reads and writes user accounts and credentials. It also stores temporary data related to user sessions and tokens.
More generally, the Curity Identity Server separates concerns and allows you to use either a single data source or work with multiple data sources. This flexibility can help when you have requirements like integrating with existing identity infrastructure, meeting data sovereignty regulations across regions or partitioning users by tenant.
The Data Management documentation provides more information on how data sources can be configured and used in various scenarios.
Getting Started#
To create a data source, navigate to Facilities → Data Sources in the Admin UI and click the New Data Source button. Then, select the type of data source you want to create and provide the required configuration properties. The following screenshot from the Admin UI shows the configuration for a PostgreSQL JDBC data source.

Data Source Types#
You can choose from many SQL, NoSQL or custom Data Sources and should be able to use the same database technology for identity data that you use for your own APIs. You can use multiple data sources and compose them in your preferred ways, each of them taking specific configuration properties to allow for tuning the behaviour.
Extensibility Points#
You can implement custom data sources using the Curity Plugin SDK and deploy them as plugins to the Identity Server, see:
- the Plugin SDK
- creating custom plugins
- creating custom data sources
The Curity Identity Server can also connect to your custom user and credential management service using:
- the generic JSON RESTful data source
- the SCIM data source
Learn More#
The Operator Data Source Training Course walks you through all the facets of setting up and operating a fast, monitored, highly-available and recoverable data source.
To learn more about advanced data source related use cases, you can also refer to the following sections: