Enterprise Relational Database Platforms

DDOSCOM helps teams implement production-grade relational database platforms for OLTP and mixed workloads, aligning schema design, replication strategy, security controls, and operating models to latency, availability, and compliance objectives.

Service overview

We turn database strategy into an executable operating model: workload-aware architecture, resilient backup and recovery posture, role-based access and auditing, and measurable performance management that supports both critical applications and downstream analytics.

Key capabilities

Capabilities focused on building relational database estates that are highly available, governable, and optimized for business-critical transaction flows.

Relational architecture and workload design

Establish robust relational foundations for transactional systems with clear boundaries for scale, consistency, and recovery.

Schema and index design for high-concurrency OLTP workloads
Read/write scaling patterns with replicas and partitioning
Connection management and query workload isolation
High-availability topology and failover architecture

Data integrity, governance, and security

Operationalize trust with enforceable controls for data integrity, access governance, and auditable change management.

Constraint strategy, referential integrity, and data quality checks
Role-based access control and privileged access management
Encryption, key rotation, and secure data-at-rest posture
Audit logging, change tracking, and compliance evidence

Operational reporting and analytics readiness

Enable reliable reporting and analytics consumption without degrading core transactional performance.

CDC-based data movement from transactional systems
Read-optimized models for KPI and dashboard consumption
Controlled publication of business-ready relational datasets
Data contracts for downstream analytics and AI pipelines

Database reliability and performance operations

Run relational environments with measurable SLOs, predictable capacity, and disciplined incident response.

Proactive monitoring for latency, locks, deadlocks, and saturation
Query tuning, index lifecycle, and execution plan governance
Capacity planning and cost-performance optimization
Runbooks, error budgets, and continuous operational improvement

Use cases

High-impact scenarios where modern relational database practices improve stability, performance, and governance outcomes.

Modernize legacy transactional estates

Refactor aging database estates to improve resilience, reduce operational toil, and sustain growth in transaction volumes.

Schema remediation and index strategy modernization
Replication and failover redesign for higher availability
Controlled migration waves with rollback safeguards
Performance baselining before and after cutover

Strengthen control in regulated environments

Implement traceable governance and security controls to satisfy internal audit, risk, and compliance requirements.

Segregation of duties and privileged access governance
Data masking and sensitive-field protection policies
Tamper-evident audit trails for operational and schema changes
Evidence-ready reporting for compliance assessments

Enable reporting without OLTP degradation

Support analytics needs while preserving transactional SLAs through workload separation and controlled data publishing.

Read replicas and extraction windows for reporting workloads
CDC streams for near-real-time operational dashboards
Business-aligned semantic models for consistent KPIs
Governed handoff to enterprise analytics platforms

Delivery model

A phased delivery model that links relational architecture decisions to uptime, risk reduction, and performance outcomes.

Assessment and target-state design

Define business priorities, current-state constraints, and target relational patterns before execution.

Workload profiling across critical applications and domains
Target architecture for availability, recovery, and scale
Risk, dependency, and change-window mapping
Phased execution plan with measurable service objectives

Implementation, operations, and optimization

Deliver modernization in controlled waves, operate with clear accountability, and optimize continuously against SLO and capacity signals.

Incremental rollout of schema, replication, and security controls
Operational model with DBA, platform, and application ownership
Recurring performance and cost-efficiency review cycles
Backlog-driven continuous reliability and quality improvements

Resources and references

Related materials to support implementation planning and accelerate decision making.

Data modernization /solutions/data-ai/data-modernization Data strategy and governance /solutions/data-ai/data-strategy-and-governance View all data solutions /our-services/view-all-data-solutions

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