PostgreSQL

PostgreSQL gives you strong guarantees where they matter: ACID transactions, referential integrity, and correctness under concurrency — the things you absolutely want when the data represents money, orders, or anything you can't afford to get wrong. Many trendier databases trade these away; Postgres keeps them without sacrificing performance.

It's also refreshingly free of lock-in. As open source, it runs anywhere — your own servers, or managed offerings from AWS RDS, Google Cloud SQL, Supabase, and others — so you're never hostage to one vendor's pricing. That flexibility protects you as you scale.

We treat the schema as a first-class part of the product. Well-modelled tables, proper constraints and foreign keys, thoughtful indexing, and migrations tracked in version control mean the database enforces correctness rather than relying on application code to remember every rule.

We pay particular attention to concurrency and data integrity — using transactions and appropriate locking so that simultaneous operations can't corrupt state or double-charge a customer. That rigor is the same whether the app is a marketplace, a fintech ledger, or an internal tool; correct data is non-negotiable.

Postgres has quietly become a capable platform for AI features too. With the pgvector extension it stores and searches embeddings for semantic search and RAG, which means many products can add AI retrieval without adopting a separate vector database — simpler architecture, one system to operate.

Its JSON support lets us mix structured and semi-structured data cleanly, and full-text search handles many search needs without a separate engine. The theme is consolidation: Postgres often does the job of several databases well enough that you don't need to run and maintain them all.