Amazon Redshift Announces Custom ODBC/JDBC Drivers and Query Visualization in the Console
Amazon Redshift’s new custom ODBC and JDBC drivers make it easier and faster to connect to and query Amazon Redshift from your Business Intelligence (BI) tool of choice. Amazon Redshift’s JDBC driver features JDBC 4.1 and 4.0 support, a 35% performance gain over open source options, and improved memory management. Amazon Redshift’s ODBC drivers feature ODBC 3.8 support, a 6% performance gain, and better Unicode data and password handling, among other benefits. Additionally, AWS partners Informatica, Microstrategy, Pentaho, Qlik, SAS, and Tableau will be supporting these Redshift drivers with their solutions. For more information please see Connecting to a Cluster in our documentation. If you need to distribute these drivers to your customers or other third parties, please contact us at redshift-pm@amazon.com so we can arrange an appropriate license.
Amazon Redshift’s new custom ODBC and JDBC drivers make it easier and faster to connect to and query Amazon Redshift from your Business Intelligence (BI) tool of choice. Amazon Redshift’s JDBC driver features JDBC 4.1 and 4.0 support, a 35% performance gain over open source options, and improved memory management. Amazon Redshift’s ODBC drivers feature ODBC 3.8 support, a 6% performance gain, and better Unicode data and password handling, among other benefits. Additionally, AWS partners Informatica, Microstrategy, Pentaho, Qlik, SAS, and Tableau will be supporting these Redshift drivers with their solutions. For more information please see Connecting to a Cluster in our documentation. If you need to distribute these drivers to your customers or other third parties, please contact us at redshift-pm@amazon.com so we can arrange an appropriate license.
The Amazon Redshift Console now helps you visualize time spent on each step of your query, so you can optimize complex queries more easily and take full advantage of our Massive Parallel Processing (MPP), columnar architecture. By going to the Actual tab of the new Query Execution Details section, you can view processing times tied to each stage or “plan node” (e.g. merge, sort, join) of a query execution plan. For more information, please see Analyzing Query Execution.