Access Relational Database with Administration Capabilities Using Teradata Client Tools
Teradata is a reliable and commonly used relational database management system for commercial databases. It can store large amounts of data—including those that are terabytes in size—making it ideal for economic data warehousing solutions and applications. If you use Teradata in your business, you can manage it easier with a web-based Teradata client. Teradata SQL client tools leverage administration capabilities by providing easy access to your relational database. With these client tools, you can create an SQL query, send it to the database, and explore the results online from a web browser.
Feature-rich and intuitive SQL editors support different kinds of databases like Teradata. Client tools for Teradata are excellent alternatives to the specialized database platform. They provide support for all of Teradata’s latest features, ranging from views and database tables to triggers, sequences, and procedures. The client tool comes with all the necessary features for filtering data, viewing database tables, and determine the total number of rows in the table. The web-based client has the same browsing features, too.
Teradata client tools simplify access to the relational database and perform administrative tasks with a data editor and web-based view manager. The latter lets you browse, filter, and view data, acquire SQL for view definition, export view data in different formats, and count the total rows. The data editor is completely online, so you can create, delete, insert, or update data, and blob or update data.
Having a Teradata SQL assistant or web edition alternative can be handy when you want to do more with Teradata. An advanced data filter can be applied to the view data and table with a few simple clicks. The online export data function lets you export the table data into PDF, insert, HTML, and CSV formats. Likewise, you can import CSV data straight to the tables. The Teradata client tool parses input CSV data columns and displays column mappings between the data columns of the uploaded CSV file and the table columns. After importing, you can save it as a job then schedule it to run at regular intervals.