Get in Touch
Get in Touch

Database Modernization

Move off legacy engines, eliminate licensing lock-in, and build a cloud-native data foundation without taking production offline.

Schedule a Discovery Call

60–90%
Reduction in licensing costs after migration

3–5×
Query performance improvement on purpose-built databases

Zero
Downtime migrations via live CDC replication

AWS
Advanced Partner — database migration expertise

Oracle · SQL Server →
Aurora
RDS
DynamoDB
Redshift
DocumentDB
PostgreSQL · MySQL
Why now

The Hidden Cost of Staying Put

Licensing fees are draining your budget. What's even less visible: the engineering hours lost to maintenance, the scalability ceiling you'll hit next quarter, and the AI capabilities you can't unlock yet.

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Runaway licensing

Oracle and SQL Server contracts scale against you. You pay for what you purchased, not what you use — and audits don't get friendlier.
Runaway licensing
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Monolithic bottlenecks

A single shared database blocks independent deployment. Every service that touches it becomes coupled — slowing releases and blocking microservices.
Monolithic bottlenecks
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Scalability ceiling

Vertical scaling has limits. Legacy databases degrade under peak load right when your business needs them most.
Scalability ceiling
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Blocked from AI/ML

Modern data pipelines need clean, accessible data. Legacy engines can't feed ML models or integrate with analytics platforms.
Blocked from AI/ML
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Engineering toil

Patching unsupported software and managing brittle schema migrations consumes senior hours that should be building product.
Engineering toil
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Vendor lock-in

Proprietary stored procedures and opaque tooling make switching feel impossible. The longer you wait, the deeper the dependency.
Vendor lock-in

The Problem

No company context
AI tools write code without knowing your codebase, your specs, your stored procedures, your standards. Generic in, generic out.

No company context AI tools write code without knowing your codebase, your specs, your stored procedures, your standards. Generic in, generic out.

Zero audit trail
Nobody knows what changed, by whom, against which spec, at what cost. When something breaks, the log is empty.

Zero audit trail Nobody knows what changed, by whom, against which spec, at what cost. When something breaks, the log is empty.

Knowledge stays siloed
The senior engineer's head is still the source of truth. The pipeline learns nothing. That person leaves, the knowledge walks out.

Knowledge stays siloed The senior engineer's head is still the source of truth. The pipeline learns nothing. That person leaves, the knowledge walks out.

Pilot never becomes default
The shiny demo works. Then adoption stalls. The new way of working never replaces the old one.

Pilot never becomes default The shiny demo works. Then adoption stalls. The new way of working never replaces the old one.

Why AIDLC?

Faster delivery
Tens of dollars per feature, hours of elapsed time. Not weeks.

Built-in compliance
Every action audited. Every dollar attributed to an issue.

Institutional memory
The pipeline learns. The org's knowledge stops walking out the door.

Faster onboarding
New engineers ramp on a pipeline that already knows the codebase. 

A pipeline that improves
Each cycle's retro feeds the next cycle's configuration.

Humans stay in control
Agents propose. Humans approve. Every merge is gated.

Problems

No company context

No company context

Zero audit trail

Zero audit trail

Knowledge stays siloed

Knowledge stays siloed

Pilot never becomes default

Pilot never becomes default

Why AIDLC?

Faster delivery

Faster delivery

Built-in compliance

Built-in compliance

Institutional memory

Institutional memory

Faster onboarding

Faster onboarding

A pipeline that improves

A pipeline that improves

Humans stay in control

Humans stay in control
What we do

End-to-End Modernization: Not Just a Migration

From assessment through design to post-cutover optimization, we handle the full programme.
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Assessment & Discovery

 

We map your schemas, stored procedures, workload patterns, and licensing costs. You get a written readiness report and prioritized backlog before any engineering begins.

SCHEMA ANALYSIS
DEPENDENCY MAPPING
COST MODELLING
Assessment & Discovery
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Target Architecture Design

 

We select and build AWS databases matched to your workloads: relational, document, key-value, or analytics. If you're moving to microservices, we design database boundaries that won't create new bottlenecks.

AURORA
DYNAMODB
DOCUMENTDB
REDSHIFT
Target Architecture Design
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Zero-Downtime Migration

 

We use AWS DMS with Change Data Capture so your source stays live throughout. For petabyte-scale datasets, we combine physical transfer with live delta sync to avoid network bottlenecks.

AWS DMS
CDC REPLICATION
SCHEMA CONVERSION
Zero-Downtime Migration
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Application Layer Refactoring

 

Stored procedures, ORM config, query rewrites. We move business logic out of the database and into application code, using AI-assisted testing to accelerate T-SQL and PL/SQL conversion.

STORED PROCEDURES
ORM UPDATES
QUERY REWRITE
Application Layer Refactoring
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Observability & Optimisation

 

Post-migration query analysis, optimizing indexes, performance tuning, and knowledge transfer. We leave you with a database you understand and can operate independently.

CLOUDWATCH
PERFORMANCE INSIGHTS
RIGT-SIZING
Observability & Optimisation
How we work

A Structured Path
to Delivery

Every project adheres to a repeatable methodology with defined checkpoints to guarantee zero production risk.
Weeks 1–2

Discover & Assess

Schema mapping, licensing audit, dependency analysis, workload assessment, and risk scoring. Detailed readiness report delivered before engineering starts.

Weeks 2–4

Architecture Design

Target architecture selection, data modeling, decomposition sequencing, rollback planning, and migration runbook. Reviewed and approved by your team.

Weeks 4–N

Migrate & Refactor

Live CDC replication, parallel validation, application layer refactoring, and staged cutover validated with defined go/no-go criteria.

Ongoing

Optimize & Observe

Performance tuning, right-sizing, query plan analysis, observability setup, and team enablement. Source systems decommissioned on your schedule.

FAQ

Can you migrate without downtime?

Yes — this is our default. We use AWS DMS with Change Data Capture (CDC) so your source database stays live throughout. We only perform a brief, planned cutover at the end, once both systems are validated and in sync.

What happens to stored procedures?

We catalogue and classify all procedural logic, then use AWS Schema Conversion Tool alongside AI-assisted refactoring to convert or move it. The goal is to migrate business logic into application code — not just re-implement it in a new engine. Scope varies by codebase, which is why discovery comes first.

How long does it take?

A focused single-database migration can complete in 6–10 weeks. A full monolith decomposition with application layer changes is typically a multi-quarter programme. We scope this clearly during assessment and phase the work so you see results incrementally.

Will we need to change application code?

Usually yes, to varying degrees. A homogeneous migration (e.g. SQL Server to RDS SQL Server) requires minimal changes. Heterogeneous migrations (e.g. Oracle to Aurora PostgreSQL) require more — query syntax, drivers, ORM config, stored procedures. We scope the application impact clearly during discovery.

What if something goes wrong at cutover?

Every migration includes a tested rollback plan. Because we use continuous replication, the source stays available right up to cutover — if a go/no-go check fails, we delay or revert with no data loss. We run integrity validation before any production traffic touches the new system.

Which databases do you work with?

Source side: Oracle, SQL Server, IBM DB2, MySQL, PostgreSQL, MongoDB, and legacy data warehouses. Target side: Amazon Aurora, RDS, DynamoDB, Redshift, DocumentDB, ElastiCache, and Keyspaces. If you have a specific combination in mind, ask us — we'll tell you honestly what's involved.

Let's Work Together