Connect to SAS Data Sets Data in Aqua Data Studio

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SAS Data Sets JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with SAS Data Sets.



Access SAS Data Sets data from tools in Aqua Data Studio such as the Visual Query Builder and the Table Data Editor.

The CData JDBC Driver for SAS Data Sets integrates SAS Data Sets data with wizards and analytics in IDEs like Aqua Data Studio. This article shows how to connect to SAS Data Sets data through the connection manager and execute queries.

Create a JDBC Data Source

You can use the connection manager to define connection properties and save them in a new JDBC data source. The SAS Data Sets data source can then be accessed from Aqua Data Studio tools.

  1. In Aqua Data Studio, select Register Server from the Servers menu.
  2. In the Register Server form, select the 'Generic - JDBC' connection.
  3. Enter the following JDBC connection properties:
    • Name: Enter a name for the data source; for example, SAS Data Sets.
    • Driver Location: Click the Browse button and select the cdata.jdbc.sasdatasets.jar file, located in the lib subfolder of the installation directory.
    • Driver: Enter the Driver's class name, cdata.jdbc.sasdatasets.SASDataSetsDriver.
    • URL: Enter the JDBC URL, which starts with jdbc:sasdatasets: and is followed by a semicolon-separated list of connection properties.

      Set the following connection properties to connect to your SAS DataSets files:

      • URI: Set this to the folder containing your .sas7bdat resources. Currently we only support local files.

      Built-in Connection String Designer

      For assistance in constructing the JDBC URL, use the connection string designer built into the SAS Data Sets JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

      java -jar cdata.jdbc.sasdatasets.jar

      Fill in the connection properties and copy the connection string to the clipboard.

      A typical JDBC URL is below:

      jdbc:sasdatasets:URI=C:/myfolder;

Query SAS Data Sets Data

You can now query the tables exposed.