// Database
PostgreSQL
Our default relational database for production applications.
5+ years hands-on experience
// Overview
How we use PostgreSQL
PostgreSQL is our default database for all applications with relational data, which is most of them. Its ACID guarantees, rich query language, JSON support, full-text search, and pgvector extension for AI workloads make it an exceptionally capable system.
// Use cases
- Transactional SaaS applications
- Multi-tenant data stores
- Financial data with ACID requirements
- AI applications with vector similarity search
- Complex reporting with window functions
// Why it matters
ACID transactions
Full transaction support with serialisable isolation, appropriate for any application where data integrity is non-negotiable.
JSON + relational
jsonb columns enable flexible schema sections within a structured relational model, no need to choose between relational and document stores.
pgvector for AI
Native vector similarity search via pgvector makes PostgreSQL the right choice for RAG applications without introducing a separate vector database.
// Production patterns
How we ship with PostgreSQL
Schema migrations run through versioned SQL or Prisma migrate, never manual prod DDL without rollback scripts.
We tune with `pg_stat_statements`, EXPLAIN ANALYZE on hot paths, partial indexes for status filters, and materialized views for reporting that can tolerate 15-minute freshness.
RDS or Aurora in production with read replicas for reporting; connection pooling via PgBouncer when serverless or high-concurrency Node workers exhaust connections.
// FAQ
PostgreSQL: common questions
PostgreSQL vs MongoDB?+
PostgreSQL default for transactional SaaS. Mongo when document shape is genuinely schemaless and relational joins are rare, we still enforce schema at application layer.
Do you use pgvector in production?+
Yes for RAG pilots under ~5M chunks; we evaluate dedicated vector stores when recall latency or scale exceeds single-node Postgres comfort.
How do you handle multi-tenancy?+
Row-level `tenant_id` with composite indexes, or schema-per-tenant for regulated isolation, decided at architecture, not retrofitted.
// Company and service positioning
Company and Service positioning is reviewed for production delivery standards by Harsha Parthasarathy (Co-Founder, Strategy & Operations 24+ years IT veteran, IBM, Global Delivery, Program Management) and Keshav Sharma (Co-Founder, Engineering and Lead Architect, Full-stack engineering, product delivery and technical standards).
// Related services