PostgreSQL rarely fails because it's the wrong database — it fails because of a schema that made sense at 10k rows, an index that was never added, or a multi-tenant model bolted on after launch. We diagnose what's actually slow, fix the schema and query patterns underneath it, and design the database to handle the scale you're growing into.
Postgres is forgiving early and unforgiving at scale. A dedicated review catches the patterns that only bite once your data grows.
We read EXPLAIN ANALYZE output, not vibes — every recommendation is backed by an actual query plan and measured before/after.
Normalization, indexing strategy, and partitioning planned for the data volume and access patterns you'll have in a year, not just today.
Row-level security, schema-per-tenant, or shared-schema with tenant_id — we pick the isolation model that matches your compliance and scale needs, not a default.
Point-in-time recovery, replication, connection pooling, and access controls checked against what actually happens during an incident.
If the fix is an index or a rewritten query, that's what we ship — we don't push a database migration to justify a bigger engagement.
The person tuning your queries has done this on production systems under load before — not learning on your database.
Scoped to what's actually slow or at risk — not a fixed audit template applied blindly.
Slow query diagnosis, index strategy, query rewrites, and connection pooling fixes for databases under real production load.
New schema design or a structured review of an existing one — normalization, constraints, and indexing aligned to actual access patterns.
Tenant isolation strategy for SaaS products — row-level security, schema separation, or shared-schema, chosen deliberately.
Major version upgrades, extension adoption (including pgvector), and schema migrations planned with rollback paths.
Point-in-time recovery setup, replication review, and access control audits so an incident isn't the first time it's tested.
Senior PostgreSQL engineers embedded in your team for a defined engagement or ongoing capacity.
Yes. Most performance engagements are scoped, fixed-cost work — we diagnose the slow queries, ship the index and query fixes, and hand over measured results. No retainer required unless you want ongoing coverage.
Yes. We scope the isolation model — row-level security, schema-per-tenant, or shared-schema with tenant_id — against your compliance requirements, expected tenant count, and query patterns, rather than defaulting to one approach.
We review point-in-time recovery, replication setup, connection access controls, and encryption at rest and in transit, then close the gaps that would actually matter during an incident — not just a checklist pass.
Yes — this is most of what we're asked to do. We start with EXPLAIN ANALYZE on the actual slow queries in your environment, not synthetic benchmarks, and fix the schema, indexes, or query structure causing it.
Tell us what's slow or what you're designing — we'll review query plans and schema, then scope a fixed approach.