A schema designed for your data
PostgreSQL rewards good design. We model your data around how it is actually queried, use the right types and constraints, and lean on Postgres features like JSONB and full-text search where they fit. A schema that matches reality keeps queries simple and the data correct, which saves you from painful migrations later.
- Modelled around real queries
- Right types and constraints
- JSONB and full-text where useful
Indexes and queries that stay fast
A slow database makes the whole product feel slow. We read query plans, add the indexes that matter, and rewrite the queries that do not scale, rather than guessing. The goal is response times that hold steady as your data grows, so you are tuning the real bottleneck instead of throwing hardware at it.
- Indexes based on query plans
- Queries rewritten to scale
- Steady response times as you grow
Scaling reads and connections
When traffic climbs, we add read replicas to spread heavy reads and put connection pooling in front so the database is not overwhelmed by too many open connections. Caching with Redis takes the hottest queries off Postgres entirely. Each step is added when the numbers call for it, not by reflex.
- Read replicas for heavy reads
- Connection pooling
- Redis for the hottest queries
Managed, backed up, on AWS
We run PostgreSQL on AWS RDS, with automated backups, encryption, and point-in-time recovery, so your data is safe and restorable. Failover is configured for availability, and access is locked down through IAM and network rules. You get a database you can trust without running it by hand.
- AWS RDS with automated backups
- Encryption and point-in-time recovery
- Locked-down access
Part of the wider stack
The data layer underpins our Django and FastAPI builds, and our approach to scalable architecture.
PostgreSQL questions
PostgreSQL is reliable, standards-compliant, and feature-rich, with JSONB, full-text search, and strong indexing. For most products it is the safe, capable default, and it scales a long way before you need anything exotic.
Yes. We profile the slow queries, read the query plans, add the right indexes, and rewrite what does not scale, then add replicas or caching if the load needs it.
On AWS RDS, with automated backups, encryption, point-in-time recovery, and failover, defined as infrastructure as code so it is repeatable and locked down.
Let's build, scale, or automate it.
Hire a full senior team or a single specialist across frontend, backend, AWS, DevOps, and AI. You work directly with the engineers, not an account manager.