Database Modernization

Modernize the Data Layer Holding You Back.

Move from legacy database dependency to a faster, validated, AI-ready data foundation that reduces licensing pressure and supports future growth.

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Your database
should power the business, not trap the budget.

Common executive pain points 

Rising licensing costs

SQL Server and legacy database renewals keep compounding, even when workloads do not grow.

Database lock-in

Critical business logic is often trapped inside schemas, stored procedures, and platform-specific dependencies.

Migration risk

Teams hesitate to move because one missed dependency can break reporting, applications, or core business workflows.

Slow assessment cycles

Manual schema reviews, dependency mapping, and conversion planning can take months before migration even begins.

Performance constraints

Legacy database environments can limit scalability, responsiveness, and the ability to support modern workloads.

AI readiness gaps

AI, analytics, and agentic workflows need clean, governed, cloud-ready data foundations to perform reliably.

SourceFuse modernizes legacy databases into validated, cloud-ready data foundations built for lower cost, stronger control, and future AI use cases.

We deliver 

SQL Server to PostgreSQL / Aurora modernization

Move from legacy SQL Server dependency to open-source, cloud-native database foundations designed for scale and flexibility.

Database assessment

Analyze schemas, stored procedures, queries, dependencies, and business logic to create a clear migration roadmap.

Dependency-aware planning

Identify application, reporting, and workflow dependencies before migration to reduce cutover risk.

Deterministic conversion

Convert database logic with structured guardrails, transparency, and human oversight — not black-box automation.

Automated validation

Use functional equivalence testing, data integrity checks, and unit tests to build confidence before production cutover.

Performance optimization

Tune the modernized database layer for scale, responsiveness, and cloud-native performance.

AI-ready data foundation

Prepare the data layer for analytics, GenAI, agentic workflows, and future intelligence use cases.

Business Impact

Lower database TCO

Reduce licensing pressure by moving from legacy database dependency to cloud-native, open-source alternatives.

Faster migration timelines

Accelerate assessment, conversion, and validation with ArcDBMigrate.

Reduced cutover risk

Validate dependencies, business logic, and data integrity before production migration.

Improved platform flexibility

Move away from platform-specific constraints and build a database foundation that can scale with business needs.

Stronger trust in migration outcomes

Use automated validation and human oversight to improve confidence before go-live.

AI-ready data layer

Create a cleaner, more modern foundation for analytics, GenAI, automation, and intelligent workflows.

customer stories

From fragmented data to measurable outcomes.

Media & Entertainment Streaming - Global

Situation

Tuned Global needed to modernize its data platform to support next-generation global streaming growth.

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Outcome

  • 10x increase in ingestion scalability
  • Supports 10M+ API traffic spikes
  • 33% reduction in database costs
  • 25% reduction in DevOps overhead

Use Case

Application Modernization/Migration

Media & Entertainment Streaming - Global
Essential Infrastructure - Australia

Situation

Service Stream needed to migrate VMware workloads to AWS-native infrastructure while reducing operational costs.

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Outcome

  • 15% reduction in annual AWS spend
  • 20% faster migration execution achieved
  • Near-zero downtime migration completed
  • AWS-native scalability and modernization enabled

Use Case

Infrastructure Modernization/Migration

service-stream-banner
Healthcare & Medical Technology - USA

Situation

Medical Tracking Solutions needed secure, scalable systems for healthcare tracking and operational visibility.

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Outcome

  • HIPAA-compliant healthcare platform modernized
  • Improved operational visibility and tracking
  • Scalable cloud infrastructure implemented
  • Enhanced platform reliability achieved

Use Case

Application Modernization/Migration

Healthcare & Medical Technology - USA
Energy & Well Engineering - USA

Situation

THF needed AI-driven engineering workflows to accelerate innovation and improve operational efficiency.

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Outcome

  • AI-powered engineering workflows implemented
  • Faster engineering decision-making enabled
  • Improved operational efficiency achieved
  • Scalable AI-ready infrastructure established

Use Case

Infrastructure Modernization/Migration

Energy & Well Engineering - USA