TeamSQL is rebranding as DataRow: Amazon Redshift Management Studio
TeamSQL has been a great platform to experiment with modern UI and powerful features to help you manage your popular databases with collaborative features.
Over two years later after launching TeamSQL in 2016, we've learned a lot about how to make database management better. As we look to the future, we want to take a more focused approach that will help us bring the best database management experience. As a result, we’re planning to rebrand TeamSQL as DataRow, starting with focusing on Amazon Redshift and say goodbye to TeamSQL. All TeamSQL services will be shut down on February 27, 2019 (00:00 UTC).
We introduced the beta of new DataRow to our Amazon Redshift users in January this year, and now it is publicly available to everyone. DataRow comes with new features, which helps you work faster. Visit DataRow's website at DataRow to learn more about how the features in DataRow can help you manage your Amazon Redshift better.
We are always here to help you switch from TeamSQL to the new DataRow with ease. Please contact us at contact us if you have any questions. See you there.
When you're working in a TeamSQL query editor window, you'll find a list of queries that you've run using that window in a sidebar located to the right-hand side.
Not only can you review the work you've done, you can easily reuse the code. Simple click on any of the snippets available and TeamSQL will automatically populate your query with the code you've chosen.
Our searches are powered by Elasticsearch, so you can be assured of finding what you need when you need it.
In the History tab, you'll have access to the Global SQL Execution History. This works like your local query history; you'll have access to the full code you wrote, regardless of whether you wrote it for Oracle,
Microsoft SQL Server,
CitusData (though you get visual indicators of which query belongs to which database engine, of course)."
Furthermore, TeamSQL caches the results returned by your queries on your local machine, so you can go back in time with rerunning the queries themselves. We do not store the results of your queries anywhere else.