Connect to Amazon S3 Data in Aqua Data Studio

The CData JDBC Driver for Amazon S3 integrates Amazon S3 data with wizards and analytics in IDEs like Aqua Data Studio. This article shows how to connect to Amazon S3 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 Amazon S3 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, Amazon S3.
   • Driver Location: Click the Browse button and select the cdata.jdbc.amazons3.jar file, located in the lib subfolder of the installation directory.
   • Driver: Enter the Driver's class name, cdata.jdbc.amazons3.AmazonS3Driver.

   • URL: Enter the JDBC URL, which starts with jdbc:amazons3: and is followed by a semicolon-separated list of connection properties.

     To authorize Amazon S3 requests, provide the credentials for an administrator account or for an IAM user with custom permissions. Set AccessKey to the access key Id. Set SecretKey to the secret access key.

     Note: You can connect as the AWS account administrator, but it is recommended to use IAM user credentials to access AWS services.

     For information on obtaining the credentials and other authentication methods, refer to the Getting Started section of the Help documentation.

     Built-in Connection String Designer

     For assistance in constructing the JDBC URL, use the connection string designer built into the Amazon S3 JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

     java -jar cdata.jdbc.amazons3.jar

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

     A typical JDBC URL is below:
     jdbc:amazons3:AccessKey=a123;SecretKey=s123;

Query Amazon S3 Data

You can now query the tables exposed.