Web App Development
PostgreSQL Web App Development With Database-First Architecture
We build web apps on PostgreSQL with the database doing the heavy lifting — proper schema design, strategic indexes, Row Level Security, and full-text search — not an afterthought ORM.
Why PostgreSQL Web App Development Beats the ORM-First Approach
PostgreSQL is the most capable open-source database ever built, and most web apps use less than 10% of what it can do. Raw SQL gets dismissed as 'too complex' in favor of ORMs that generate terrible queries — multiple joins expressed as nested objects, N+1 patterns that multiply database calls with list size, and missing indexes that make those queries slower as data grows. PostgreSQL features like window functions for analytics, CTEs for readable complex queries, tsvector for full-text search, JSONB for flexible metadata, and partial indexes for filtered subsets can eliminate entire microservices that would otherwise be needed.
Database schema design is the most consequential architectural decision in web app development and the one most frequently rushed. A poorly designed schema — missing foreign keys that allow orphaned records, denormalized data that gets out of sync, composite keys that prevent efficient indexing, text fields where an enum would enforce valid states — creates performance and correctness problems that compound over time. We design PostgreSQL schemas with data integrity enforced at the database level, not just the application layer, and migration paths planned for the features on your near-term roadmap.
PostgreSQL performance at scale requires understanding query plans, index usage, connection pooling, and VACUUM behavior. The vast majority of web app performance problems we investigate trace to the same three causes: queries that cannot use indexes due to implicit type casting or function calls in WHERE clauses, N+1 query patterns where a list of 100 records triggers 100 separate database queries, and connection exhaustion because connection pooling was not configured. We address all three proactively — before they become production incidents.
Our Approach to Postgresql web app development
Every project follows our 4-step vibe-coding process — AI handles the boilerplate, senior engineers handle the craft. From idea to live product in 3–7 days for MVPs.
Discovery
We model your domain in an entity-relationship diagram before designing the database schema. We identify which queries will be most frequent, which data grows fastest, and which relationships need referential integrity enforced. We also identify which data will need full-text search, geographic queries, or time-series aggregation — each changes the schema design significantly.
Design
We design the PostgreSQL schema with normalization, referential integrity, check constraints, and indexes as first-class design decisions — not implementation details. Every foreign key relationship is explicit. Every enum field uses a PostgreSQL enum type or a CHECK constraint. Every column that will appear in a WHERE clause has an index strategy.
Build
Schema migrations in versioned SQL files checked into Git, Row Level Security for access control, PostgreSQL full-text search with tsvector and tsquery for search features, PostgreSQL functions for complex aggregations that run faster in the database than in application code, and connection pooling via Supabase PgBouncer configured for your expected concurrency.
Launch
Pre-launch database review: EXPLAIN ANALYZE on every query in the critical path, index usage verified, no table scans on large tables, connection pool configured for 3× expected concurrency. We also run a synthetic load test on the database independently to identify query performance before frontend traffic makes it hard to isolate.
What You Get
Every postgresql web app development engagement includes these deliverables — scoped before we start, delivered before we invoice.
- PostgreSQL schema in versioned SQL migration files with complete rollback scripts
- Entity-relationship diagram documenting all tables, relationships, and constraints
- Row Level Security policies for all tables with user-scoped access requirements
- Indexes: B-tree, GIN for full-text search, GiST for geographic queries, partial indexes
- Full-text search implementation with tsvector columns and tsquery search functions
- PostgreSQL functions for complex business logic: aggregations, computed columns, triggers
- Connection pooling via Supabase PgBouncer configured for production concurrency
- EXPLAIN ANALYZE report for all critical-path queries with optimization applied
- Audit log tables with trigger-based population for compliance requirements
- Database backup and point-in-time recovery configuration via Supabase
Tech Stack We Use
PostgreSQL web app development at Greta treats the database as the most important layer of the stack — because it is. We use Supabase to manage PostgreSQL with the full feature set: Row Level Security for access control, tsvector for full-text search, PostGIS for geographic queries, JSONB for flexible structured metadata, and pg_cron for scheduled jobs. Schema is managed with SQL migration files in version control — no ORM-generated migrations that produce opaque SQL. We use the pg JavaScript client directly for queries that need raw SQL performance and Supabase's typed client for standard CRUD operations where the type generation is valuable. Query plans are reviewed before launch, not after performance complaints.
Case Study
FinTrack — Financial Data Architecture on PostgreSQL
FinTrack's core engineering challenge was maintaining a consistent, accurate transaction ledger across concurrent bank account webhook deliveries — a classic database consistency problem. We designed the PostgreSQL schema with a double-entry-inspired transaction model: every financial event produces two records (a debit and a credit) in the same transaction, enforcing balance consistency at the database level via a CHECK constraint. We used PostgreSQL's SERIALIZABLE isolation level for the import pipeline to prevent race conditions on concurrent webhook deliveries. Full-text search on transaction descriptions used tsvector indexes that returned results in under 10ms on a 100,000-row transaction table. The schema has never required a migration for correctness since launch.
Read full case studyPricing Transparency
PostgreSQL web app development is our standard database approach on every project — we do not charge extra for using PostgreSQL over a document database. Projects start at $5,000 for MVP scope. Database audit and optimization engagements for existing PostgreSQL applications start at $2,000 for a EXPLAIN ANALYZE review and index optimization report. All projects include schema documentation and connection pooling configuration.
MVP
From $5,000
3–7 business days
Full Build
From $15,000
2–4 weeks
All projects include full code ownership, two revision rounds, Vercel deployment, and one week of post-launch support. No hidden fees.
Frequently Asked Questions
Why do you use PostgreSQL instead of MongoDB or Firebase?
PostgreSQL enforces data integrity constraints — foreign keys, check constraints, not-null requirements — that document databases cannot. For 95% of web apps, the data has relational structure: users have orders, orders have items, items have prices. Relational structure belongs in a relational database. We use PostgreSQL on every project and have never encountered a use case where a document database would have been a better choice.
Do you use an ORM or write SQL directly?
We use a hybrid approach. For standard CRUD operations, we use Supabase's typed JavaScript client, which generates TypeScript types from the schema. For complex queries — aggregations, multi-table joins, window functions, full-text search — we write SQL directly. We avoid ORM-generated SQL for complex queries because it is rarely optimal and difficult to optimize when it is not.
How do you handle database migrations?
We use SQL migration files checked into Git. Each migration has an up and down script — applying the change and rolling it back. Migrations run in order at deployment time. We never apply schema changes directly to the production database without a corresponding migration file. This means the schema in production always matches the schema in the codebase.
How do you design indexes for performance?
We add a B-tree index to every column that appears in a WHERE clause with a high cardinality. For text search, we use GIN indexes on tsvector columns. For queries that filter on a subset of rows, we use partial indexes that are smaller and faster than full-table indexes. We run EXPLAIN ANALYZE on every critical query to verify index usage before launch.
Can you optimize an existing slow PostgreSQL database?
Yes. We offer a database performance audit: EXPLAIN ANALYZE on your slowest queries, index gap analysis, N+1 query detection, and connection pool assessment. The audit produces a prioritized list of optimizations. Most database performance issues can be fixed with indexes and query rewrites without schema changes.
How do you handle full-text search in PostgreSQL?
We use PostgreSQL's built-in tsvector and tsquery for full-text search. We add a tsvector column to each searchable table, populate it with a trigger function that runs on insert and update, and create a GIN index on it for fast search queries. For simple search over a single language, this approach is faster and cheaper than Elasticsearch or Algolia for most web app scales.
What connection pooling do you use?
We configure PgBouncer via Supabase's built-in connection pooler. PgBouncer maintains a fixed pool of PostgreSQL connections and queues application requests, preventing the connection exhaustion that occurs when each API request opens a new database connection. We configure the pool size based on your expected concurrency and the query execution time distribution.
How do you handle database backups?
Supabase maintains automated daily backups with point-in-time recovery available on the Pro plan. We document the backup retention period and test the restore process before launch. For financial or healthcare applications with stricter recovery requirements, we configure additional backup exports to an S3-compatible bucket.
Ready to ship?
Ready to build your PostgreSQL web app?
Start Your ProjectOr reach us directly at hello@greta.agency
Written by the Greta Agency team · Last updated April 2025