Compare CA Datacom vs. Rocket Data Virtualization

Ensure your business applications are continuously accessible by leveraging a dependable database system designed for enterprise-level, high-volume workloads with exceptional fault tolerance. The CA Datacom® suite, along with its various rDBMS offerings, serves as the robust repository you need. This resilient database system takes advantage of zIIP specialty processor technology, resulting in enhanced and economically efficient database management. It facilitates seamless integration with mobile-to-mainframe initiatives, cloud services, web applications, and big data analytics through JDBC and ODBC interfaces. Effectively handle high-volume workloads, while each new version incorporates advanced hardware technologies and refined memory optimization strategies. Database Administrators and Systems Programmers can easily monitor and manage their environment by querying the Dynamic System Tables within a Multi-User Facility region on a specific LPAR, utilizing contemporary tools. Furthermore, modern developers who may be new to the mainframe environment can efficiently manage their source code using popular modern IDEs like Visual Studio Code or Eclipse CHE, bridging the gap between traditional and contemporary development practices. This capability not only enhances productivity but also fosters innovation within the organization.

Hybrid data stacks create duplication and delay: mainframe records, on prem apps, and cloud platforms often end up with mismatched copies, brittle ETL, and long lead times for “just one more feed.” Moving large datasets for every use case is slow, costly, and expands the security surface. Rocket® Data Virtualization™ is a data virtualization and federated query solution that enables a governed, virtual data model across mainframe, distributed, and cloud sources—so BI tools, analysts, and applications can query sensitive data in place. Key capabilities: • Federated SQL queries/joins across heterogeneous sources with pushdown • Standard connectivity (e.g., JDBC/ODBC/REST) for BI, analytics, and apps • Virtual views/semantic layer to simplify access and reuse logic • Centralized security controls, auditing, and masking (where supported) • Optional caching/materialization to balance performance and freshness Result: faster time to data with less ETL and lower migration risk.