backend // stack
The database that refuses to store bad data.
Indexes, constraints, and query profiling protect transactional integrity as data and traffic grow. Launches and campaigns become non-events instead of outages.
Use as the system of record for anything relational; pair with Redis for ephemera.
why we use it
(01) Constraints over hope
Foreign keys, uniqueness, and check constraints reject invalid writes at the boundary, not in a cleanup script months later.
(02) Indexes with evidence
Every hot query ships with EXPLAIN output reviewed in CI. N+1 queries die in review instead of on launch day.
(03) One store, many jobs
Full-text search, JSONB documents, and advisory locks cover most needs without adding a second database to operate.
scope
(01) Schema with foreign keys and integrity constraints
(02) Indexed hot paths verified with query plans
(03) Full-text search without an external service
(04) Point-in-time backups with tested restores
tradeoffs
Our default versus the common alternative, stated honestly.
| dimension | 2sh | traditional |
|---|---|---|
| Integrity | Invalid writes rejected by the database itself | Validation only in frontend code that drifts |
| Performance | Indexes and connection discipline before traffic arrives | Unindexed queries discovered during the outage |
| Scope | Search, JSON, and queues in one operated store | Four datastores for a problem one solves |
| When not Postgres | Ephemeral counters and job payloads live in Redis | Caching relational reads because queries were never tuned |
Not sure PostgreSQL fits your estate?
In the audit we map your estate, model the cost of staying versus moving, and document the recommendation in writing.