Data & Storage
PostgreSQL as the system of record you can trust for a decade
An open-source relational database with genuine ACID guarantees, deep SQL, JSONB flexibility and vector search — the default system of record for serious business data.
ACID
Guaranteed transactional correctness
0 licence
Open source, no per-core fees
<100ms
P95 query target after index tuning
PITR
Point-in-time recovery on managed deployments
Definition
What PostgreSQL is
PostgreSQL is a mature relational database supporting transactions, constraints, advanced indexing, partitioning, replication and extensions such as PostGIS and pgvector — combining relational rigour with document and vector capabilities.
When to use it
Where PostgreSQL is the right call
Recognise your situation before committing engineering budget.
Capabilities
How we work with PostgreSQL
What is actually delivered, beyond the logo on a stack slide.
Schema design
Normalised models with constraints that make invalid business states impossible.
Performance tuning
Index strategy, query plan analysis, partitioning and connection pooling.
Security
Row-level security for tenant isolation, encryption at rest and least-privilege roles.
Extensions
pgvector for embeddings, PostGIS for geospatial, full-text search without a second engine.
Strengths
- Strongest correctness guarantees of the mainstream open databases
- JSONB gives document flexibility without abandoning SQL
- Widest BI and reporting tool compatibility
- Available managed on every major cloud and on-premise
Trade-offs to plan for
- Vertical scaling limits eventually require partitioning or read replicas
- Connection-heavy applications need pooling (PgBouncer) to behave
- Schema changes on large tables need online-migration planning
Use cases
PostgreSQL in production
Representative systems we build and support on this technology.
ERP and finance core
Ledgers, stock movements and documents with referential integrity enforced in the database.
Multi-tenant SaaS
Row-level security isolating tenants without duplicating databases.
AI retrieval store
pgvector embeddings sitting alongside the business records they describe.
Comparison
PostgreSQL vs MySQL vs MongoDB
| Dimension | PostgreSQL | MySQL | MongoDB |
|---|---|---|---|
| Transactional integrity | Excellent | Good | Document-scoped |
| Advanced SQL features | Extensive | Moderate | N/A |
| JSON support | JSONB, indexed | Basic | Native |
| Vector / AI search | pgvector | Limited | Atlas Vector Search |
Engineering practices
Non-negotiables on every engagement
Decision guide
Which direction fits your situation?
Match your constraints to the recommended approach.
| If this sounds like you | We recommend |
|---|---|
| Any system of record with money or stock | PostgreSQL with enforced constraints |
| Multi-tenant SaaS isolation | PostgreSQL with row-level security policies |
| AI retrieval next to business data | PostgreSQL with pgvector, avoiding a separate vector database |
Delivery
Services built on PostgreSQL
Pairs well with
Industries running this
FAQ
PostgreSQL questions, answered
Related technologies
What we usually pair with it
MongoDB
A document database for varied, evolving or high-volume data — catalogues, events, content and IoT telemetry that never fit neatly into fixed tables.
Odoo
A modular open-source ERP covering finance, sales, inventory, manufacturing and HR — configured first, extended only where your process is genuinely different.
Docker
Reproducible application images that remove "works on my machine" from the vocabulary and make deployments boring in the best possible way.
Planning a build or migration on PostgreSQL?
Share your requirements and current systems. We will return an architecture recommendation, trade-offs and a phased plan — under NDA.