Ab Initio Co>Operating System is used for data integration, ETL processes, and complex data transformations. It is robust in handling large-scale data processing and batch processing, offering scalability, reliability, and performance for managing heavy workloads.
Ab Initio Co>Operating System provides real-time data processing capabilities, an intuitive meta-programming environment, and efficient batch job execution. Users appreciate its flexibility in supporting various data sources and platforms. Primary use cases involve addressing complex data transformations and integration needs, enhancing productivity and efficiency.
What are the key features of Ab Initio Co>Operating System?
- Scalability: Efficiently handles large-scale data processing and batch processing.
- Robust Parallel Processing: Delivers powerful ETL capabilities with strong performance.
- Intuitive Drag-and-Drop Interface: Simplifies creating and managing data workflows.
- Flexible Data Integration: Supports diverse data sources seamlessly.
- Error Handling and Debugging: Features strong tools for managing and resolving issues.
- Automation: Automates repetitive tasks, streamlining operations.
- Seamless Integration: Easily integrates with other tools, enhancing workflow efficiency.
What benefits and ROI should be considered?
- Performance: High reliability and performance in managing heavy workloads.
- Efficiency: Real-time data processing enhances productivity and decision-making.
- Scalability: Efficient scaling to meet growing data processing needs.
- Flexibility: Supports a wide range of data sources and platforms.
- Usability: Intuitive interface and automation reduce learning curve and improve efficiency.
Industries implement Ab Initio Co>Operating System for its reliable data integration and ETL capabilities. Financial services use it for processing large volumes of transactional data, while retail sectors apply it for real-time analysis of customer data. Healthcare organizations leverage its robust processing for managing patient records and data aggregation.
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.
