Postgres is the foundation of every serious web application. The schema decisions made at the start compound for years.
A Postgres developer who understands indexing, query optimization, and schema design makes the difference between a database that holds up under load and one that requires expensive rewrites at scale. Fixed-price projects, not hourly billing.
Web application with a database that's getting slow, with queries that time out, or designed by someone who didn't know Postgres well enough to optimize it for production traffic
Postgres is the right database for most web applications. It's relational, ACID-compliant, supports JSON where needed, and scales to very large datasets with proper indexing and query design. The problem is that Postgres is easy to use badly.
The most common Postgres mistakes in production applications:
Missing indexes. A query that returns 10 rows from a table with 10,000 rows works fine without an index. The same query on a table with 10 million rows requires a sequential scan that takes 30+ seconds. Indexes on foreign keys, on filtered columns in frequent queries, and on ORDER BY columns are required — not optional.
N+1 query patterns. An ORM like Prisma or Drizzle makes it easy to write code that issues one query per row in a result set. A list of 100 orders that each trigger a separate query for customer data issues 101 queries. The equivalent JOIN query issues 1. The difference is imperceptible in development; it's a 100× performance difference in production.
Bad schema design. Wide tables with nullable columns, storing JSON where relational data would be more queryable, or designing the schema for the first use case without anticipating the queries that come later. Schema migrations on large tables are expensive and risky.
No connection pooling. Serverless functions that open a new Postgres connection per request exhaust the connection limit quickly. PgBouncer or Neon's built-in connection pooling is required for serverless deployments.
Postgres schema designed for production: indexed correctly, normalized appropriately, with query performance that holds up under real load
Schema design
Normalized schema designed for the application's actual query patterns. Tables, relationships, and constraints that enforce data integrity at the database level.
Index strategy
Indexes on every foreign key. Composite indexes for multi-column filters. Partial indexes for filtered queries. Covering indexes for query-critical columns.
Query optimization
EXPLAIN ANALYZE on slow queries. Index additions, JOIN rewrites, or query restructuring to get query times into milliseconds.
Migration management
Schema migrations via Drizzle or Prisma migrate. Safe migration practices for production tables.
Connection pooling
PgBouncer configuration or Neon serverless driver configuration for serverless deployments.
One honest number to start.
Fixed-scope, fixed-price. The number below is the starting point — final scope is built from your brief.
Postgres schema designed for production: indexed correctly, normalized appropriately, with query performance that holds up under real load
Three steps, every time.
The same repeatable engagement on every project. No surprises, no mystery, no billable ambiguity.
Brief & discovery.
We send you questions, then get on a call. Output: a written scope with every step, feature, and integration listed.
Build & ship.
Fixed schedule, weekly reviews. No scope creep unless you change the scope — and if you do, we reprice it transparently.
Warranty & retainer.
30-day warranty on every launch. Most clients stay on a monthly retainer for ongoing features and maintenance.
Why Fixed-Price Matters Here
Database work has defined scope: the schema, the indexes, and the queries. Fixed price.
Questions, answered.
Neon for serverless Next.js deployments (branching, serverless scaling, connection pooling built in). Supabase if you want the built-in auth and real-time subscriptions. Self-hosted (AWS RDS) for large-scale applications where you need specific instance types. The right answer depends on scale and operational complexity tolerance.
Index every foreign key column on creation. Foreign key columns that aren't indexed create sequential scans on every JOIN, and JOIN performance is central to relational database applications.
Schema + API + application: from $25k. Fixed-price.
Tell Ryel about your project.
Describe what you’re building and what outcome you need. You’ll have a written, fixed-price scope within the week.