What products are in the DataCat Catalyst Suite?

The suite includes DB2 Catalyst for DB2 to PostgreSQL modernization, Oracle Catalyst for Oracle source readiness and DDL evidence, and Sync Control for provider-governed replication and cutover evidence.

Does DataCat support Oracle to PostgreSQL migration?

Oracle Catalyst supports the source-readiness lane: Oracle source profiles, catalog inventory, DBMS_METADATA DDL evidence, readiness reporting, and conversion-risk triage. It does not claim native Oracle CDC or full automated PL/SQL parity.

How does DataCat compare to Ora2Pg, AWS DMS Schema Conversion, and Ispirer?

Those tools can be direct converters or migration utilities. DataCat focuses on the governed project record around the migration: source posture, retained artifacts, validation evidence, operator workflow, and application-team handoff.

What is the current DB2 Catalyst scope?

DB2 Catalyst is the deepest current lane, covering DB2 source onboarding, schema and data movement, validation evidence, cutover posture, and application handoff for PostgreSQL programs.

Is DataCat self-hosted?

Yes. DataCat is designed for customer-hosted deployment so source profiles, DDL artifacts, validation evidence, and project records stay inside the buyer's infrastructure boundary.

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DataCat Production Scope: DB2 and CDC to PostgreSQL Modernization

AI Data Catalyst Engineering · 2026-04-26 · 8 min

The current DataCat production scope: DB2 catalog and extract ingestion, PostgreSQL migration execution, validation evidence, IBM CDC companion readiness, application handoff, and the boundaries that still require customer or partner validation.

Current Product Scope

DataCat is a self-hosted DB2 to PostgreSQL modernization workbench. The product is designed for enterprise teams that need more than a data mover: they need source inventory, conversion artifacts, migration execution, validation evidence, cutover readiness, and downstream application handoff.

The current delivery path supports DB2 source metadata and staged extract workflows, PostgreSQL target execution, row-count and aggregate validation, project-scoped artifacts, and operator-facing evidence. IBM CDC is treated as a companion lane: DataCat imports readiness and status evidence instead of claiming to replace IBM's log-based replication stack.

What DataCat Owns

DataCat owns the DB2 data-modernization lane:

DB2 catalog and DDL analysis
PostgreSQL DDL candidates and conversion evidence
Stored procedure candidates with review gates
COBOL copybook and record-layout context where artifacts are supplied
Staged source CSV migration into PostgreSQL
Validation evidence tied to the exact source files and target tables
IBM CDC companion readiness and cutover packets
Application mapping artifacts for downstream build teams

This is intentionally narrower and stronger than claiming to modernize the entire mainframe by itself. CICS, IMS, JCL, RACF, reporting, scheduler modernization, and application rewrites remain customer, SI, AWS Transform, or specialist-partner lanes. DataCat packages the DB2 evidence those teams need.

Production Boundaries

The current product should not be positioned as native generic CDC, fully automated COBOL or JCL conversion, a compliance certification product, or a guaranteed procedure-conversion substitute for engineering review. It is a governed migration workbench with automation, evidence, and review gates.

For production deployment, teams should validate:

DB2 connectivity path, TLS, driver packaging, and read-only privileges
Source extract naming and staged file handling
PostgreSQL version, extensions, roles, and target schema policy
IBM CDC or replication-provider ownership when low-downtime cutover is required
PHI/sensitive-data handling and customer control implementation
Application regression tests and first-write smoke tests
Backup, restore, observability, and support runbooks

Why This Wins

Competitors usually own one layer: CDC, schema conversion, cloud DMS, or consulting delivery. DataCat is strongest where those layers meet. It makes the migration record coherent: what was found, what was converted, what was loaded, what validated, what remains risky, and what application teams should build against next.

That is the production claim: a better DB2-to-PostgreSQL modernization workbench, not a magic button.