OpenText Structured Data Manager

OpenText Structured Data Manager is the database lifecycle product inside the OpenText Cybersecurity Data Security pillar. It handles three operational shapes that regulated database operations need: archival of cold data out of production into managed archive stores, masking of sensitive data for non-production environments, and lifecycle management of database content across retention, legal hold, and disposal. The product covers Oracle, SQL Server, DB2, PostgreSQL, MySQL, and SAP databases as the major sources.

Archival is where production performance lives. Most enterprise databases accumulate cold data (orders from five years ago, transaction histories, audit logs) that no application is actively reading but that compliance requires keeping. Production database performance degrades when those rows sit alongside hot data, and archive solutions that move data out without preserving accessibility break compliance retrieval. Structured Data Manager moves cold rows to archive stores while keeping the data accessible through the same query interface, so production stays fast and audits stay possible.

Masking is for non-production environments. Developer environments, QA environments, and analytics sandboxes need realistic data to be useful, but cannot legally hold the production-shaped regulated data they would otherwise need. Structured Data Manager masks data on copy: production tables get copied to non-production with sensitive fields replaced by realistic-but-fake values that maintain referential integrity. Compare to Imperva DSF and Delphix on this capability; Structured Data Manager is the OpenText answer.

What stalls Structured Data Manager adoption is operational scope creep. The product covers archival, masking, and lifecycle, and programs sometimes try to do all three at once. The cleaner shape is to scope by use case (archive Oracle financial systems first, mask SQL Server analytics environments next, layer lifecycle policy on top later) and run each one as a discrete program with clear acceptance criteria. Merito's engagement scopes by use case and sequences the rollout so the program ships value at each step rather than trying to deliver everything at once.

Merito has watched programs adopt Structured Data Manager and try to deliver archival, masking, and lifecycle policy in one twelve-month rollout. The result is partial coverage on all three. The cleaner shape is to scope by use case and sequence: archive Oracle financial systems first, mask SQL Server analytics environments next, layer lifecycle policy on top later. Each step ships value; the program does not stall waiting for the last step.

Merito recommends Structured Data Manager specifically when programs run regulated database content at scale, when SAP archival is in scope, and when database lifecycle (retention, disposal, legal hold) is a compliance driver. For programs needing database activity monitoring as the lead capability, Imperva DSF is often stronger; for programs needing virtualized non-production data, Delphix is often stronger. Merito surfaces those alternatives honestly.

The Voltage SecureData integration is the load-bearing add when masked data needs additional protection. Programs that mask data and then expose the masked stores to broad audiences sometimes find that the masking is reversible by inference; layering FPE or tokenization on top closes that exposure.