Database Architecture for Solution Architects Training Course

Course overview

Solution architects must make database decisions that remain sound when transaction volumes rise, reporting demands expand, cloud services change, and several delivery teams depend on the same data. A weak choice of data model, persistence pattern, replication approach, or ownership boundary can produce costly rework, slow releases, inconsistent records, and systems that cannot meet recovery or regulatory obligations. This course equips architects to turn business, integration, performance, and resilience requirements into defensible database architecture decisions.

Participants examine relational, document, key-value, graph, and event-oriented persistence models in the context of real solution architectures. They learn to define data domains and ownership, model transactional and analytical workloads, select fit-for-purpose database technologies, design schemas and indexes, plan partitioning and replication, and specify backup, recovery, security, and observability controls. The course also addresses data consistency trade-offs, CAP considerations, API and event integration patterns, and architecture decision records (ADRs) for database choices.

Instructor-led sessions combine architecture briefings with design reviews, SQL and modelling exercises, and a multi-system case study. Working in architect teams, participants produce a database architecture pack for a representative business platform: context and data-flow diagrams, a logical data model, technology selection rationale, non-functional requirement traceability, resilience design, and implementation recommendations. This deliverable can be adapted as a practical template for architecture reviews and project initiation.

The course is designed for solution architects working across application, integration, cloud, and data teams who need to make database decisions without becoming full-time database administrators. It is particularly valuable where organisations are modernising legacy estates, decomposing monoliths, introducing cloud data services, or integrating operational and analytical platforms.

Course objectives

By the end of this course, participants will be able to:

• Assess workload characteristics using transaction, latency, volume, availability, and consistency requirements
• Translate business capabilities into data domains, ownership boundaries, and lifecycle rules
• Design logical data models with entities, relationships, keys, constraints, and audit attributes
• Select relational, document, key-value, graph, or event persistence patterns using a documented decision matrix
• Model indexing, partitioning, replication, and caching strategies for defined performance scenarios
• Specify recovery point, recovery time, encryption, access-control, and retention requirements for a database platform
• Evaluate database integration designs using APIs, change data capture, events, and data synchronisation patterns
• Produce an architecture decision record and database architecture pack for a solution proposal

Benefits of attending

Target competencies

Who should attend

• Solution Architects — who must justify database technology and data-design decisions across delivery teams
• Enterprise Architects — who define technology guardrails, reference architectures, and data-platform standards
• Technical Architects — who translate non-functional requirements into deployable persistence and resilience designs
• Cloud Architects — who select and govern managed database services across cloud workloads
• Lead Software Engineers — who shape service boundaries, schema designs, and application data-access patterns
• Data Architects — who align operational data stores, integration flows, and analytical consumption needs

Requirements and prerequisites

Participants should have practical experience contributing to software, integration, cloud, or data solution designs. They should understand basic SQL concepts, including tables, primary keys, joins, and simple queries, and be familiar with common application architecture concepts such as APIs, services, environments, and non-functional requirements. Experience reading an entity-relationship diagram and discussing availability or performance requirements is helpful. No database administration certification, advanced query tuning expertise, programming language proficiency, or prior hands-on experience with PostgreSQL or MongoDB is required. The course explains platform-specific features through architecture exercises rather than operational administration tasks.

Training methodology

The instructor uses short architecture briefings followed by worked examples, facilitated design critiques, and hands-on modelling tasks. Participants analyse a running case involving customer, order, payment, and reporting workloads, then compare relational and NoSQL options against explicit quality attributes. Exercises use PostgreSQL, pgAdmin, MongoDB Compass, and diagramming templates to inspect schemas, indexes, query plans, and replication choices. Small groups conduct architecture review boards, challenge assumptions, and refine a final database architecture pack with an individual workplace application plan.

Course outline

Day 1: Database architecture decisions and workload discovery

• Database responsibilities within a solution architecture
• Operational, analytical, search, cache, and event-store workload classifications
• Quality attribute scenarios for latency, throughput, availability, and data retention
• Transaction boundaries and consistency requirements
• CAP theorem and practical consistency trade-offs
• Data domain decomposition and bounded-context ownership
• Database architecture decision records and decision matrices

Workshop: Participants analyse a business platform brief and produce a workload inventory, quality-attribute scenarios, and initial data-domain map.

Day 2: Data modelling and persistence pattern selection

• Conceptual, logical, and physical data model distinctions
• Entity-relationship modelling with cardinality, optionality, and business keys
• Normalisation, denormalisation, and controlled data duplication
• Relational database design for transactional systems
• Document, key-value, graph, and time-series data-model patterns
• Event sourcing, CQRS, and append-only event-store considerations
• Technology selection criteria for managed and self-managed databases

Workshop: Participants create a logical data model and complete a technology selection matrix for customer, order, catalogue, and payment domains.

Day 3: Performance, scale, and availability design

• Index structures, selectivity, and query access paths
• Reading PostgreSQL EXPLAIN plans for architectural decisions
• Schema patterns for high-write and high-read workloads
• Horizontal partitioning, sharding, and tenant-isolation approaches
• Read replicas, multi-region replication, and failover topology
• Caching patterns and cache-consistency risks
• Capacity assumptions, growth forecasts, and performance test criteria

Workshop: Participants inspect sample queries in pgAdmin, recommend indexes and partitioning, and draw a high-availability deployment topology.

Day 4: Integration, security, and data lifecycle controls

• Service-owned databases and shared-database anti-patterns
• API-based data access and schema contract management
• Change data capture, outbox pattern, and event publication
• Data synchronisation, conflict handling, and idempotency
• Encryption in transit, encryption at rest, and key-management responsibilities
• Role-based access control, row-level security, and audit logging
• Backup, restore, retention, archival, and deletion design

Workshop: Participants design an integration and control model that connects operational services to reporting while documenting security and recovery requirements.

Day 5: Architecture governance and solution design workshop

• Database observability metrics, logs, traces, and alert thresholds
• Recovery point objective and recovery time objective design
• Data migration, schema evolution, and backward-compatible change strategies
• Cloud managed-service trade-offs, cost drivers, and vendor constraints
• Architecture review checklists for database proposals
• ArchiMate views for data stores, services, and information flows
• Communicating database risks, assumptions, and recommendations to stakeholders

Workshop: Participants assemble and present a complete database architecture pack, receive peer review, and produce an ADR-backed action plan for their own environment.

Tools & standards covered

PostgreSQL, pgAdmin 4, MongoDB Compass, ArchiMate 3.2

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions