Compare Adabas & Natural vs. Rocket Data Virtualization in 2026

Rocket Data Virtualization

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Description

In a world characterized by rapid transformation, securing a visionary partner is essential for navigating the future. You require someone who can guide you in evolving your robust Adabas & Natural applications well into the year 2050 and further. For decades, Adabas & Natural have been your reliable backbone for achieving results. Now, envision a future where you can maximize that investment and leverage the distinctive business logic ingrained in your essential applications. We stand ready to be that partner, dedicated to facilitating the digital modernization of your legacy systems swiftly and without risks. Together, we can address the generational shift in developers, enhance your applications to reduce expenses, broaden the accessibility of your core applications, and speed up development within a cutting-edge environment. Rely on advanced Adabas & Natural technologies to streamline your IT landscape and modernize your applications quickly and safely. Embrace new opportunities with APIs, transition Adabas & Natural to the cloud, attract fresh developer talent through DevOps practices, and reduce costs by transferring mainframe workloads to zIIP. By taking these steps, you position your organization to thrive in a rapidly evolving digital landscape.

Description

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.