Oracle to PostgreSQL Migration Blueprint

Overview

Oracle Database is a mature commercial RDBMS with deep PL/SQL stored-procedure logic, proprietary data types, and high license costs. PostgreSQL is an open-source RDBMS that now matches most Oracle features, so migrating cuts licensing spend and avoids vendor lock-in. This blueprint converts schema, server-side code, and data while keeping the application correct.

The hardest part is rarely the data itself. It is the embedded business logic: packages, triggers, sequences, hierarchical CONNECT BY queries, and Oracle-specific functions such as NVL, DECODE, and SYSDATE. Plan for code conversion to dominate the timeline.

Phases

Assessment. Inventory schemas, objects, and dependencies. Run AWS Schema Conversion Tool (SCT) or ora2pg to produce a compatibility report that estimates manual effort. Catalogue PL/SQL packages, materialized views, and partitioning.

Schema conversion. Map data types: NUMBER to numeric/bigint, VARCHAR2 to varchar, DATE to timestamp, CLOB to text. Replace sequences-plus-triggers with GENERATED ... AS IDENTITY. Recreate indexes and constraints.

Code migration. Rewrite PL/SQL packages as PL/pgSQL functions. Replace DECODE with CASE, NVL with COALESCE, and CONNECT BY with recursive CTEs. Adjust application data-access code for driver and SQL dialect differences.

Data migration. Bulk-load static data with ora2pg or COPY. For live systems, set up change data capture (CDC) so PostgreSQL stays current during the conversion window.

Cutover. Validate row counts and checksums. Run the application in read-only verification mode against PostgreSQL, then flip writes during a planned window or via a near-zero-downtime CDC switchover.

Optimization. Tune autovacuum, work_mem, and shared_buffers. Add the partitioning and indexes that match the new planner's behavior; PostgreSQL costs queries differently than Oracle.

Key Risks and Mitigations

• Data consistency: Validate with row counts, per-column checksums, and sampled diffs. Use CDC to keep deltas small.
• PL/SQL incompatibility: Some constructs have no direct equivalent. Triage early; rewrite high-value logic and retire dead code.
• Downtime: Use CDC-based replication (e.g., Debezium plus a target loader) to minimize the cutover window.
• Skills gap: PostgreSQL operations differ from Oracle. Train DBAs on vacuum, WAL, and replication before cutover.

Recommended Tooling

ora2pg for schema and data assessment and conversion; AWS SCT for automated code translation reports; Debezium for CDC; pgbench for load testing; pg_stat_statements for query tuning.

Success Metrics

Track license-cost reduction, p95 query latency parity or improvement, zero data-integrity defects after validation, and reduced post-cutover incident count.

Prerequisites

Complete schema inventory, a representative test data set, a CDC-capable replication path, and rollback plan. Establish performance baselines on Oracle before you begin so you can prove parity.