We are pleased to share that DataRow is now an Amazon Web Services (AWS) company. We're proud to have created an innovative tool that facilitates data exploration and visualization for data analysts in Redshift, providing users with an easy to use interface to create tables, load data, author queries, perform visual analysis, and collaborate with others to share SQL code, analysis, and results.. Together with AWS, we look forward to taking our tool to the next level for customers.

Amazon Redshift System Tables

See the records of all system tables in one place without performing any additional query, and understand how your Amazon Redshift system behaves.

System Tables in DataRow contains information about how the system is functioning. You can view these tables without having to write any SQL.

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System Tables in DataRow contain information about how the system is functioning. You can view these tables without querying your database.

The following Amazon Redshift system tables views in DataRow can be helpful in troubleshooting data load issues:

  • STL_LOAD_ERRORS to discover the errors that occurred during specific loads.
  • STL_FILE_SCAN to view load times for specific files or to see if a specific file was even read.
  • STL_S3CLIENT_ERROR to find details for errors encountered while transferring data from Amazon S3.


STL_LOAD_ERRORS Table displays the record of all of the load errors on Amazon Redshift. List all errors and review their reasons with error descriptions.


STL_FILE_SCAN table returns the files that Amazon Redshift read while loading data via the COPY command. List all files and see the loading times of each in detail.


STL_S3_CLIENT_ERROR records errors encountered by a slice while loading a file from Amazon S3. List each error with their error reasons.

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Whether you’re looking for a Private Cloud or Enterprise solution, DataRow has the resources and expertise to help you achieve more with your Amazon Redshift.

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