PostgreSQL database services — audit, tune, or design from scratch
Production Postgres at fintech (GigEasy) and AI tooling (Instill). Schema review, query tuning, index strategy. Monthly subscription.
Who this is for
Product team whose Postgres is the bottleneck — slow queries, wrong indexes, bloated tables.
The pain today
- No DBA; the backend dev is guessing at EXPLAIN plans.
- Vacuum and autovacuum are mysterious, pg_stat_statements not enabled.
- N+1 queries are the default; eager loading is theoretical.
- Backups and restore are 'RDS automated backups and pray'.
The outcome you get
- A senior engineer who has shipped Postgres at fintech and AI tooling scale.
- Schema review plus query tuning plus index strategy, written down.
- Backup and point-in-time-recovery plan tested end to end.
- Migrations pipeline (Prisma, Liquibase, Flyway, or native) decided.
Services the Postgres engagement covers
A Postgres engagement covers: schema review (normalization, constraints, JSONB use, partial indexes, partitioning, enum vs lookup tables), query tuning (slow-query log, pg_stat_statements, auto_explain, EXPLAIN ANALYZE on the top 20 queries), index strategy (btree vs GIN vs BRIN vs partial, covering indexes, index-only scans), migrations pipeline (Prisma, Liquibase, Flyway, or plain SQL with rollback plans), backups (pg_basebackup, WAL-E or WAL-G, point-in-time recovery), replication and read replicas when the scale justifies it, and observability (structured logs, Postgres exporter for Prometheus, slow-query alerting).
GigEasy plus Instill — two Postgres production references
GigEasy runs Laravel plus PostgreSQL plus Redis as the fintech MVP stack. Postgres decisions there — JSONB for the flexible onboarding payload, partial indexes on the user-state columns, queue tables separated from transactional data — shipped the 3-week MVP without a DBA on the team. Instill runs Postgres as the primary store at Vercel — 1,000+ skills saved, clean schema with tight foreign keys, migration pipeline with rollback-on-failure. Both are production Postgres at different scale points and both use the same discipline (every query measured, every index justified, every migration reversible).
Three fixes that show up in almost every Postgres audit
Fix one: enable pg_stat_statements and auto_explain. You cannot optimize what you cannot measure, and most teams have neither enabled. Fix two: review the top 20 queries by total_exec_time (not count). Most teams tune for the frequent queries and ignore the infrequent-but-expensive ones, which is usually where the real time lives. Fix three: index strategy review. Missing indexes are common; so are over-indexing (writes pay the cost) and wrong-column-order composite indexes. Those three together usually recover 50 to 80% of Postgres performance issues without changing application code.
Pricing and engagement model
Applications subscription at $3,499 per month flat covers ongoing Postgres work as part of a broader application engagement. Audit-only engagements (written report, tuning plan, no implementation) bill against the Advisory rate at $4,500 per month pro-rated for 1 to 3 week scope. Both deliver written output you can hand to your team.
Recent proof
A comparable engagement, delivered and documented.
Built and shipped an investor-ready MVP from scratch
Built the entire technological base and delivered MVP in just 3 weeks, enabling a successful rapid launch and investor demo.
Frequently asked questions
The questions prospects ask before they book.
- Which Postgres versions do you target?
- Postgres 14, 15, 16. Current greenfield work is on 16. Legacy app upgrades from 12 or 13 are common and part of the monthly engagement.
- Managed (RDS, Aurora, Supabase, Neon) or self-hosted?
- Managed by default — RDS, Aurora, Supabase, Neon, or Crunchy Bridge. Self-hosted only when there is a specific reason (compliance, cost ceiling, on-prem requirement).
- pgvector for vector search?
- Yes. pgvector is a real production option for RAG and semantic search under 100M vectors. Above that, a dedicated vector store (Pinecone, Weaviate) starts earning its price.
- Replication strategy?
- Primary plus one or two read replicas for read-scaling. Logical replication for zero-downtime version upgrades. Streaming replication for failover. The audit picks what the app actually needs — not what looks impressive.
- Do you do Postgres on Kubernetes?
- Rarely recommend it. Managed Postgres (RDS, Aurora, Supabase, Neon) is almost always cheaper and more reliable than Postgres on K8s. Exceptions are rare and get justified in writing.
Ready to start?
Tell me what you need in 60 seconds. Tailored proposal in your inbox within 6 hours.