A database records the facts on which a digital service depends. Good design preserves meaning, protects integrity and supports change without turning every new requirement into a risky migration.
Data usually outlives the applications built on top of it. A well designed database keeps information accurate, protects privacy and supports new features for many years.
We design databases that enforce business rules, perform well under growth and remain understandable to both engineers and analysts.
Model meaning before storage
Tables and documents should represent clear business concepts, ownership and lifecycle. Constraints belong close to the data when they protect universal rules. A shared vocabulary helps product, engineering and reporting teams interpret the same information consistently.
Plan every schema change
Production data changes require compatibility, rehearsal and recovery. Expand and contract patterns allow old and new application versions to coexist during a transition. Backups matter only when restoration is tested and recovery responsibilities are known.
Optimise from evidence
Indexes, queries and caching should respond to measured workload. Premature optimisation can increase write cost and operational complexity. Slow query evidence and realistic data volumes show where improvement will produce the greatest benefit.
Modelling the real domain
Tables and relationships should reflect real business entities and rules. Constraints such as primary keys, foreign keys, unique rules and checks let the database itself protect data quality, even when application code has bugs.
Choosing the right database type
Relational databases suit most business data thanks to strong consistency and flexible queries. Document stores help with rapidly changing structures, key value stores with caching, search engines with full text search and time series databases with metrics. Many products combine two or three types deliberately.
Indexing and query performance
Indexes make common queries fast but slow down writes and consume storage. Teams should analyse real query patterns, review execution plans and add indexes where they bring clear benefit. Monitoring slow queries in production reveals new needs as the product evolves.
Security, backup and migration
Access should follow the principle of least privilege, with row level security where users share tables. Automated backups, point in time recovery and tested restores protect against mistakes. Schema changes should be applied through versioned migrations reviewed like code.
Recommended technology
Tools we use and why
PostgreSQL
Feature rich relational database with row level security and extensions.
MySQL
Widely supported relational database for web applications.
MongoDB
Document database for flexible and nested structures.
Redis
In memory storage for caching and fast counters.
Elasticsearch
Full text search and log analytics.
Supabase
Managed PostgreSQL with authentication, storage and realtime features.
Step by step approach
How we deliver it
- 1Document entities, relationships and business rules with stakeholders.
- 2Select database types based on access patterns and consistency needs.
- 3Design schemas with constraints and clear naming.
- 4Add indexes based on real query patterns.
- 5Configure access control, encryption and backups.
- 6Manage every schema change through versioned migrations.
Avoid these
Common mistakes
- Storing everything as unstructured text or generic key value pairs.
- Skipping foreign keys and constraints for perceived speed.
- Adding indexes on every column without measurement.
- Changing production schemas manually without migrations.
Measure success
Key metrics
- Core queries completing under 50 milliseconds.
- Successful restore tests at least every quarter.
- Zero data integrity incidents caused by missing constraints.
- Storage growth forecast and reviewed monthly.
Practical priorities
What technology leaders should carry forward
- Make business meaning explicit in the model
- Rehearse migrations and restoration
- Tune performance from real workload evidence
Questions answered
Frequently asked questions
Should we use SQL or NoSQL?
Most business applications are best served by a relational database, with specialised stores added for specific needs.
How do you migrate data from an old system?
We map old and new models, write repeatable migration scripts, validate results thoroughly and run rehearsals before the final switch.
How do you keep personal data safe?
Through access control, encryption, row level security, data minimisation and careful audit logging.
SJ Dev Technologies perspective
A trusted database is not merely fast. It keeps business facts consistent, supports controlled evolution and gives teams evidence when performance decisions are required.