CloverETL vs ViaSQL by Adaptigent comparison

CloverETL is a rapid, end-to-end data integration solution. Businesses choose CloverETL for its usability and intuitive controls, along with its lightweight footprint, flexibility, and processing speed. Achieving true, rapid data integration means much more than just raw data processing power. Rapid refers to an end-to-end process that begins the moment a data-related problem is recognized to the point when the data is in the right place and form to be analyzed and monetized.

ViaSQL enables powerful data extraction from complex sources through standard SQL queries. It provides direct access to all your system databases, allowing teams to seamlessly manage enterprise data with ease. The powerful tool opens bi-directional access to both mainframe and distributed data sources, enabling rapid web and cloud application development. Gone are the days of complex and time-consuming legacy data management practices!

Direct Access to Data Sources

With ViaSQL, you can directly access mainframe data using ODBC or JDBC. The native read/write conversion functionality allows you to access both relational and non-relational databases with SQL queries, so your teams don’t need to know anything about mainframe databases.

Call Out From Mainframe Applications

ViaSQL also makes outbound calls from legacy applications by providing COBOL and PL/I access to distributed data sources. It allows for true bi-directional data access from the mainframe without the need to modify any legacy system code.

Bulk Transfer Capabilities

ViaSQL allows you to move large amounts of data between the mainframe and relational databases. It eliminates the need for other expensive and complex Extract, Transform, and Load (ETL) systems when copying mainframe data to modern data lakes and warehouses.

Combine Direct and Indirect Data Sources

When used with Adaptive Integration Fabric, ViaSQL allows you to combine direct and indirect data sources by creating workflows that pull data via mainframe applications, as well as directly from data sources. This allows users to not only create highly efficient data extraction systems but also expose data to modern systems such as REST or SOAP APIs.