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§ Services / Database Migration

Database migration, run as engineering — not as a project gamble.

Move from complex legacy databases to modern platforms or the cloud on a predictable timeline. Automated conversion where it makes sense, engineered review where it does not.

A. SUPPORTED PLATFORMS

Source and target coverage.

Common migration routes across the enterprise database landscape — relational, columnar, document, and cloud-native targets.

DB2 LUW DB2 z/OS DB2 for i Informix Progress Oracle SQL Server Sybase ASE Sybase IQ Teradata MySQL MariaDB PostgreSQL MongoDB AWS Azure Firebird InterBase
B. WHEN TO CALL US

If any of these sound familiar, we can help.

Tight deadlines, fuzzy timelines

A board commitment exists, but every estimate from the team sounds like a different number. You need a credible date, not another range.

Stalled or stop-start delivery

The migration has been on the roadmap for a while now, and progress is non-linear. Each restart costs context and institutional patience.

No in-house migration practice

Strong DBAs, strong app teams — but no one whose full-time job is moving data from one database engine to another at enterprise scale.

Lack of end-to-end ownership

Tools have been bought, vendors have been engaged, but no single party is on the hook for the outcome. The seams are where projects die.

FIG. DATA FLOW

Source to target, with dual-write before cutover.

Change data capture keeps source and target in lock-step. We dual-write and validate for a full cycle before the cutover window, then run target as primary with source kept hot until rollback is no longer needed.

FIG. 02 — MIGRATION DATA FLOW ILLUSTRATIVE
SOURCE · LEGACY DB2 / ORACLE JOURNAL / REDO Production traffic ● LIVE · UNTIL CUTOVER CDC PIPELINE EXTRACT log mining TRANSFORM schema map VALIDATE · ROW HASH · ROW COUNT · LAG paired runs · drift alarms DUAL-WRITE for one business cycle TARGET · MODERN PostgreSQL WAL / STREAM Shadow primary PROMOTE ON CUTOVER CDC apply CUTOVER & ROLLBACK CONTROL Runbooks · DNS / connection-string flip · source kept hot for N days
C. THE PROCESS

Seven stages. One operating discipline throughout.

01

Assessment

Access, kick-off, written migration plan, statement of work. The output is a document you can take to your steering committee.

02

Migration build

Schema conversion, data migration testing, integrity testing, and any application-side changes — API translation, embedded SQL, business logic shifted to the application layer where appropriate.

03

Manual review and corrections

The five percent of conversion that automation cannot handle on its own. Engineered fixes, internal validation, and documentation of every deliberate departure from the source.

04

Functional testing

Snapshot environments built from production data, application and database tested end-to-end, all logical issues resolved before performance work begins.

05

Performance testing

Load profiling, converted-code review, refactoring, and targeted optimization. We are not done until the new system matches or exceeds the performance envelope of the old one.

06

Production data migration

The real cutover dataset, moved under change control with full verification. Reconciliation reports go to your team before any switch decisions are taken.

07

Cutover

Database and application switch under a documented runbook, user access enabled in waves, system startup supervised by the same engineers who built the migration.

D. BEYOND THE CONVERSION

Services that surround the migration itself.

D.01

Database audit

Structured review of the current environment to surface inefficiencies, hotspots, and migration blockers before any code is written.

D.02

Embedded SQL migration

End-to-end SQL statement migration so the application keeps talking to the new database the same way it talked to the old one.

D.03

Database API conversion

Translating database APIs so the integration layer remains intact while the engine underneath changes.

D.04

Logic migration to app layer

Selective relocation of business logic from stored procedures to the application tier where doing so improves scalability and long-term maintainability.

D.05

Deployment and integration

Installation, configuration, and integration into your cloud or on-premises stack, with the new system properly seated in your operations.

D.06

Performance optimization

Post-conversion engineering to extract throughput, reduce cost-per-query, and bring the new platform up to its full performance envelope.

D.07

Refactoring

Restructuring of program code without changing its external behavior — making what worked yesterday easier to maintain tomorrow.

D.08

Target technology consulting

Independent guidance on which target platform best addresses the limitations of the current one — without product to sell.

D.09

Support and testing

Standing maintenance, performance review, and quality assurance that survive the moment the migration is declared "done".

E. OUTCOMES

What changes after the cutover.

A working plan, not a slide

A long-term modernization sequence, owned by named engineers, revisited at quarterly architecture review.

Better performance, fewer incidents

Modern engines with active security maintenance and a smaller incident surface than the system they replaced.

Less data sprawl

Consolidation of critical data into a smaller number of well-understood stores, with deliberate retention strategy.

Cost back in your budget

Lower-cost engines, leaner ops, and a maintenance footprint that no longer dictates the rest of your IT roadmap.

§ 06 — Begin

Ready to model what independent support looks like for your estate?

Fixed-fee two-week assessment. We deliver a renewal-trajectory model, risk grading, and a written recommendation — yours to keep, no obligation.