Tactical Edge
AWS database modernization

Assess the database estate, choose the right AWS destination, test source-to-target behavior, and control cutover from one delivery plan. The first automated path supports Oracle to PostgreSQL.

Reference architecture

Tactical Edge AWS Database Modernization Factory

We use AWS DMS for supported full-load and change data capture paths. When workload scale, engine compatibility, or the downtime model calls for a different method, we use an appropriate engine-native backup, restore, or bulk-load path. Conversion and testing remain separate, visible workstreams.

Source estate

Oracle
Db2 and SAP ASE
SQL Server
Teradata and Netezza
MySQL and PostgreSQL

Database Modernization Factory

01

Estate assessment

02

Target evaluation

03

Conversion remediation

04

Business parity testing

05

Cutover coordination

06

Post-cutover stabilization

Migrate

AWS DMS or engine-native transfer

Convert

DMS SC, AWS Transform, AWS SCT

Assure

Test results, controls, approvals

AWS destinations

Aurora PostgreSQL
Amazon RDS
Oracle Database@AWS
Amazon Redshift

Data migration

AWS DMS handles supported full-load and CDC routes. Engine-native backup, restore, export, import, or bulk-load utilities are used when they provide a safer or faster fit.

Schema and application conversion

DMS Schema Conversion, AWS Transform, and AWS SCT address supported conversion work. Tactical Edge resolves remaining database objects and affected application SQL through reviewed changes.

Factory assurance and cutover

The collector, validation harness, CloudWatch checks, Step Functions gate, test records, and named approvals show whether the migration is ready. We rehearse the source freeze, endpoint switch, rollback, and stabilization steps for your application.

Reusable Factory accelerators

The tools behind the offering

These reusable tools run in the environment your team selects and produce reviewable results for architecture, migration testing, and cutover decisions. The current collector and validation path supports Oracle to PostgreSQL. We add other engine paths after testing them against the source technology.

Built from the assets you control. We migrate your schemas, database code, data, exports, and documentation to the chosen AWS target. We do not copy a database product. Your project data is used only for your migration, with the access and data-use settings your team approves.

Evidence flow

Each stage produces an artifact the next gate can verify.

Fail-closed controls
01

Collect

Inventory JSON

Read-only source evidence

02

Validate

Parity report

Required checks pass

03

Deploy

AWS control plane

Versioned infrastructure

04

Gate cutover

Named decision

Evidence plus approval

Assessment Collector

Runs read-only Oracle and PostgreSQL inventory queries, maps database objects and dependencies, and produces a reviewable AWS target shortlist without storing credentials.

Validation Harness

Compares source and target results for selected queries, row sets, and business totals, then reports what is ready for cutover and what still needs work.

AWS Deployment Templates

Creates a DMS full-load-and-CDC task, encrypted test records, approval state, least-privilege functions, logs, and a Step Functions control plane.

Cutover Orchestrator

Checks DMS status, table validation, CDC latency, business-parity tests, and a named human decision before the cutover gate can pass.

Factory workspace

Your migration team can review assessment findings, test results, and cutover decisions in the read-only workspace.

Open secure workspace
Your team controls cutover: the orchestrator verifies readiness and records approval. Named owners use the application runbook to stop source writes, change endpoints, and decide when rollback infrastructure can be removed.

Six delivery workstreams

From incomplete inventory to verified production

Each workstream produces a concrete decision or deliverable. Start with an assessment, test one representative workload in a pilot, then reuse the same controls across migration waves.

Estate assessment

Build a read-only inventory of engines, versions, schemas, procedural code, application connections, jobs, change rates, and reporting dependencies.

Dependency map and migration waves

Target evaluation

Compare rehost, replatform, and refactor paths across Aurora PostgreSQL, RDS, Oracle Database@AWS, and Amazon Redshift.

Target decision with cost and risk

Conversion remediation

Ingest AWS conversion reports, resolve unsupported objects, identify affected application SQL, and route high-risk changes for review.

Source-controlled remediation backlog

Business parity testing

Test data, queries, stored procedures, transactions, business totals, and performance against temporary target environments.

Repeatable functional-equivalence test report

Cutover coordination

Configure AWS DMS movement, rehearse sequencing, watch replication lag, record approvals, and preserve explicit rollback points.

Rehearsed cutover and rollback runbook

Post-cutover stabilization

Watch query regressions, locking, connections, storage, backups, recovery, cost, and service parameters through the agreed stabilization period.

Production-readiness and optimization report

Supported migration lanes

AWS destination options by source workload

Oracle does not always mean Aurora. A warehouse does not belong on an OLTP target. The assessment compares compatibility, operational model, modernization value, downtime, conversion effort, and cost before recommending a path.

SourceAWS destination optionsOffering laneWhere the work concentrates
Oracle OLTPAurora PostgreSQL, RDS PostgreSQL, RDS for Oracle, or Oracle Database@AWSFlagship pathTarget selection, PL/SQL remediation, application dependencies, and functional proof carry the most value.
Oracle data warehouseAmazon RedshiftAdjacent pathAdds ETL, BI, distribution, sort strategy, workload replay, and performance work to the database move.
Db2 and SAP ASEAurora PostgreSQL or RDS PostgreSQLSpecialist pathDeep procedural logic and limited legacy expertise create high remediation and assurance needs.
SQL ServerAurora PostgreSQL, RDS PostgreSQL, or BabelfishAssurance pathFocus on unsupported applications, complex features, control requirements, and independent parity testing.
Teradata, Netezza, and GreenplumAmazon RedshiftWarehouse pathThe migration includes scripts, ETL, BI dependencies, reconciliation, workload management, and tuning.
MySQL and PostgreSQLAurora or RDS, same engineStandardized pathWell suited to version upgrades, consolidation, managed operations, and faster migration packages.

Fixed-scope offering

Database Migration and Modernization Assessment

Start with one representative workload or a broader database estate. We assess the current environment, compare viable AWS targets, identify migration and conversion work, and produce a testable modernization plan before implementation begins.

  • Read-only estate and dependency inventory
  • Target recommendations for the workloads we assess
  • Conversion and application impact analysis
  • Cutover, rollback, effort, and pilot plan
Contact us about an assessment

A confidence score backed by tests

Conversion percentage is not enough. The pilot reports what compiled, what passed functional tests, what matched the source, what met performance targets, and what still needs human remediation.

Pilot test report

Object

compile status

Query

result parity

Business

reconciliation

Workload

performance

Frequently asked questions

Plan the route before starting replication

Does the Database Modernization Factory replace AWS DMS?

No. AWS DMS and DMS Schema Conversion provide managed migration, replication, conversion, and data validation capabilities. The Factory adds reusable assessment, business-parity tests, AWS deployment templates, and an approval-gated cutover control plane, plus delivery work for application dependencies, unresolved conversions, rehearsals, and stabilization.

Does every Oracle workload move to Aurora PostgreSQL?

No. The assessment compares Aurora PostgreSQL, RDS PostgreSQL, RDS for Oracle, Oracle Database@AWS, and Amazon Redshift based on workload behavior, Oracle-specific dependencies, modernization goals, downtime, risk, and cost.

What does the first engagement deliver?

The fixed-scope assessment delivers a database and application dependency inventory, target recommendation, conversion analysis, application impact report, downtime architecture, migration waves, risk and effort estimate, and a scoped pilot proposal.

How is migration correctness tested?

The validation harness compares selected source and target queries, row sets, and business totals using explicit tolerances. We add procedure, transaction, application, and workload tests for your system. Required test failures block the cutover gate, and named owners review high-risk exceptions.

Bring one representative database

We will assess the source, compare AWS targets, identify the last-mile conversion work, and define a pilot that proves parity before you commit the full estate.

Start the assessment