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Data & application architecture
Database Systems Integration
Integrate relational, document, and in-memory data stores into web applications. Design data access around the workload, consistency requirements, and operational needs rather than treating every database as interchangeable.
01 / Application contexts
Where this stack fits.
Examples of project contexts and delivery patterns this technology can support.
01Repository-backed stack
Relational business systems
Transactional data models for users, finance, inventory, orders, and workflow records.
02Repository-backed stack
Document-oriented data services
Flexible document storage for application records and catalogues.
03Repository-backed stack
Caching and search layers
Use Redis for fast key-value access and Elasticsearch for indexed search workloads.
02 / Technology
The tools for the job.
A practical selection of technologies used to plan and deliver this kind of work.
PostgreSQLMySQLMariaDBMongoDBSQLiteRedisElasticsearchPrismaSequelizeMongoose
01
Relational schema design
Model tables, constraints, indexes, and transactional relationships.
02
Document data modelling
Design MongoDB collections and indexes around application access patterns.
03
Cache and search integration
Coordinate Redis caching and Elasticsearch query workflows.
04
Migration and backup planning
Apply controlled schema changes and operational recovery practices.
03 / Outcomes
What this technology helps you achieve.
The outcome is a dependable foundation that can support your audience and business goals.
Data integrity
Schema and transaction choices help preserve business rules.
Workload-aware storage
Select relational, document, cache, or search systems for the right job.
Operational resilience
Migrations, indexing, and recovery planning support maintainable data services.
04 / Process
A clear path from brief to delivery.
Each stage helps keep expectations, feedback, and delivery aligned.
Assess data access patterns
Map entities, query volume, consistency, and search requirements.
Select database engines
Choose PostgreSQL, MySQL/MariaDB, MongoDB, SQLite, or Redis based on the workload.
Design schema and access
Implement indexes, constraints, caching, and repository boundaries.
Validate and operate
Test data integrity, migrations, query performance, and recovery plans.
Next step
Let's shape the right scope for your project.
Tell me what you need and what success looks like. We can work through a practical plan.