Why PostgreSQL?
PostgreSQL is the database you choose when you want to get things right from the start. It handles relational data with full ACID compliance, but it also supports JSONB for document-style storage, arrays, full-text search, geographic queries with PostGIS, and even vector embeddings for AI applications. This versatility means fewer moving parts in your infrastructure; one database often replaces what would otherwise require Elasticsearch, Redis, and a separate document store.
PostgreSQL's query planner is sophisticated enough to handle complex joins and aggregations efficiently. Its extension ecosystem (pg_stat_statements, pgvector, TimescaleDB) addresses specialized needs without switching databases.
The database has proven reliability across decades of production use. When you build on PostgreSQL, you build on a foundation that will handle your scale requirements for years.
Our Approach
We design schemas with normalization as the starting point and denormalize strategically where query performance demands it. Every table gets a primary key strategy decided upfront: UUIDs for distributed systems, sequential IDs for simpler setups.
Indexes are planned based on actual query patterns, not guesswork. We use EXPLAIN ANALYZE to verify that indexes are being used as intended and optimize queries iteratively based on real production data.
Migrations are versioned and reversible. We write them to be safe for zero-downtime deployments: adding columns as nullable first, backfilling data, then adding constraints. Row Level Security policies handle multi-tenant data isolation at the database level when using Supabase or similar platforms.
Real-World Application: PttAVM Clone
PttAVM Clone uses PostgreSQL to handle marketplace data: products, sellers, orders, and reviews. The schema demonstrates patterns we apply across projects.
Database patterns implemented:
- Multi-tenant data model with seller isolation
- Full-text search for product discovery
- JSONB columns for flexible product attributes
- Proper indexing for common query patterns
- Prisma ORM for type-safe database access
Performance remains consistent as product catalogs grow because queries are optimized from the start.
When to Choose PostgreSQL
PostgreSQL is the right default for most applications. It handles everything from a startup's first hundred users to enterprises processing millions of transactions daily.
Choose a different database when you have specific requirements PostgreSQL does not address well: globally distributed databases with single-digit-millisecond writes across continents (CockroachDB or Spanner), pure key-value caches (Redis), or graph databases for heavily connected data (Neo4j). For the vast majority of web applications, PostgreSQL covers your needs today and scales with you tomorrow.
Our Track Record
We have designed and optimized PostgreSQL databases for applications across industries. Our work includes schema design for multi-tenant SaaS platforms, query optimization that reduced page load times from seconds to milliseconds, and migration strategies that moved legacy MySQL databases to PostgreSQL without downtime. We monitor query performance continuously and tune indexes and configurations as usage patterns evolve.
FAQ
Should we use PostgreSQL or MySQL? PostgreSQL for new projects. It has better standards compliance, more features (JSONB, arrays, full-text search), and stronger data integrity defaults. MySQL is fine for existing projects, but there is no reason to choose it for new development.
How do you handle database migrations in production? Through versioned migration files that can run during deployment without downtime. We use expand-contract patterns: add new columns as nullable, migrate data, then add constraints. Prisma Migrate or raw SQL migrations depending on project complexity.
What about connection pooling? Essential for serverless and high-concurrency applications. We use PgBouncer or Prisma's built-in connection pool depending on deployment architecture. Connection limits are configured based on expected concurrency.
How do you approach multi-tenant database design? Row Level Security for shared-schema multi-tenancy (simpler, more cost-effective). Schema-per-tenant when data isolation requirements are strict. The choice depends on compliance requirements and expected tenant count.
Can you help optimize slow queries? Yes. We analyze query plans with EXPLAIN ANALYZE, identify missing indexes, optimize join orders, and restructure queries. Performance improvements of 10-100x are common when addressing poorly optimized queries.
Related Solutions
PostgreSQL powers our data layer:
- Prisma ORM Development - Type-safe database access
- Supabase Development - Managed PostgreSQL with auth and real-time
- Node.js Development - Backend application code
- SaaS Development - Multi-tenant data architecture
- Fintech Development - ACID-compliant financial data