Data modelled for the long run
Database Architecture
Every slow app we've ever rescued had the same root cause: a data layer designed in a hurry. We model your data properly the first time — or untangle it the second time — across PostgreSQL, MongoDB and the caching layers between them.
What's included
- Relational modelling & indexing strategy in PostgreSQL
- Flexible document design & aggregation in MongoDB
- Query profiling and performance tuning
- Zero-downtime migrations & replication setups
- Caching architecture with Redis
- Backup strategy & disaster recovery drills
Why it matters
What you get beyond the code
Queries that stay fast
Indexes and schemas designed around your real access patterns — not just what the ORM generates.
Migrations without downtime
Expand-and-contract migration patterns mean schema changes ship while your product keeps running.
The right store for the data
Relational where consistency matters, documents where flexibility wins, cache where speed counts.
Ready for the worst day
Tested backups, point-in-time recovery and documented runbooks — because untested backups aren't backups.
FAQ
Common questions
Usually PostgreSQL — it handles relational and JSON workloads brilliantly. MongoDB shines for genuinely document-shaped data and horizontal scale. Many of our builds use both, each where it's strongest.
Related services
Often paired with this
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