ROVQIX provides PostgreSQL schema design, indexing and query optimisation, and zero-downtime migrations — for teams whose application has slowed down as data grew, or whose original schema no longer fits what the product became.
Almost every slow application we audit has the same three causes: a missing index, an N+1 query pattern, and a schema that made sense for the first version of the product.
pg_stat_statements first
Expand and contract
For real query shapes
Every migration
Finding what is actually slow using real statistics and execution plans, rather than the query someone suspects.
Indexes matched to real query shapes, with unused and duplicate indexes removed — they cost write performance.
Normalisation where it protects correctness, denormalisation where it is measurably needed, constraints throughout.
Expand-and-contract migrations that run without downtime and without locking a large table for minutes.
Pooling configured correctly, which is the usual cause of mysterious failures under load in serverless setups.
Backups with point-in-time recovery and — critically — an actual tested restore, not an assumed one.
| Cause | Symptom | Typical fix |
|---|---|---|
| Missing index | One endpoint slow, worsening over time | Add a matched index |
| N+1 queries | Slow lists, fine detail pages | Eager loading or a join |
| Sequential scans | Whole app slows as rows grow | Index, or rewrite the query |
| Connection exhaustion | Intermittent failures under load | Pooling configuration |
| Lock contention | Timeouts during writes | Shorter transactions |
| Unbounded result sets | Memory spikes, timeouts | Pagination with limits |
Expand and contract: add the new structure, write to both, backfill, switch reads, then remove the old structure — each step independently deployable.
Each step is reversible on its own. A rename done in a single migration is not — and on a large table it can lock writes for long enough to constitute an outage.
PostgreSQL is the right default for the large majority of web applications. It handles relational data, JSON documents, full-text search and geospatial queries competently, with transactions and constraints protecting correctness.
PostgreSQL primarily, plus MySQL, MongoDB and Redis. We will tell you honestly if your database needs a specialist we are not — Oracle and SQL Server work, for instance, is outside what we do.
Partially. We can review schema, queries and code. But real optimisation needs real statistics — a read-only replica or an anonymised copy with representative data volume is usually enough.
Adding a correct index to a query doing a sequential scan on a large table routinely produces improvements of two or three orders of magnitude. Others need query or schema changes for more modest gains. The audit gives you specifics.
Yes — managed services versus self-hosted, instance sizing, replicas, backup strategy and cost. Managed PostgreSQL is the right answer for most teams, and we will say when it is not.
Indicative ranges in USD. Every engagement is quoted to a written scope before work starts, so the number you approve is the number you pay.
$1,800 – $4,000
1 week
Best for: An application that has become slow
$4,000 – $15,000
2–8 weeks
Best for: Implementing the fixes properly
$2,500 – $7,000
1–3 weeks
Best for: New products or a major redesign
How we think about this work, in more depth.
Databases
A 30-minute call, then a written proposal with scope, price and timeline within two to three working days. No retainer required to get a real number, and no obligation if the answer is that we are not the right fit.