PostgreSQL Development

A relational database that handles far more workloads well than most teams expect.

What PostgreSQL is

PostgreSQL is an open-source relational database with strong guarantees around transactions and data integrity. It enforces constraints at the database level, so invalid data cannot enter regardless of which application writes it.

Its extension ecosystem widens its range considerably — JSONB for document-style data, PostGIS for geospatial queries, pgvector for embedding search, TimescaleDB for time-series. One database often covers needs that would otherwise require several.

Suitability

When PostgreSQL is the right choice

And when it is not. Choosing the wrong tool costs more than any implementation detail.

Good fit for

Data with meaningful relationships and integrity requirements
Anything involving financial records or transactions
Mixed workloads combining relational, JSON, geospatial or vector data
Teams wanting one database rather than several specialised stores

Consider alternatives for

Extremely high write throughput of simple key-value data, where a purpose-built store fits better
Pure caching, which belongs in Redis
Genuinely schema-less data with no stable shape at all

In practice

What we build with PostgreSQL

Primary application data

The main store for most systems we build, with constraints enforced in the schema.

Multi-tenant isolation

Row-level security enforcing tenant boundaries at the database rather than in every query.

Vector search

pgvector for retrieval alongside relational data, avoiding a separate vector database in many cases.

Considerations

Things worth knowing

Practical notes from running this in production.

Connection handling needs attention at scale — pooling via PgBouncer or an equivalent is usually required.
Indexes are the single largest performance factor, and the most common cause of slow queries is a missing one.
Major version upgrades need planning; managed services simplify this considerably.

FAQ

Common questions

PostgreSQL or MongoDB?

PostgreSQL unless you have a specific reason otherwise. Most application data has relationships and benefits from enforced integrity, and JSONB covers document-shaped data well. MongoDB fits when documents are genuinely independent and the schema varies unpredictably.

Can PostgreSQL handle our scale?

Almost certainly. It comfortably handles workloads far larger than most applications generate. Performance problems attributed to Postgres are usually missing indexes, inefficient queries or connection exhaustion rather than the database itself.

Let’s talk about your PostgreSQL project

Tell us what you are trying to build or fix. We will come back with scope, approach and an honest view on cost and timeline.

What PostgreSQL is

PostgreSQL Development

What PostgreSQL is

When PostgreSQL is the right choice

Good fit for

Consider alternatives for

What we build with PostgreSQL

Primary application data

Multi-tenant isolation

Vector search

Things worth knowing

Common questions

PostgreSQL or MongoDB?

Can PostgreSQL handle our scale?

Explore further

Let’s talk about your PostgreSQL project

Looking for something specific?

PostgreSQL Development

What PostgreSQL is

When PostgreSQL is the right choice

Good fit for

Consider alternatives for

What we build with PostgreSQL

Primary application data

Multi-tenant isolation

Vector search

Things worth knowing

Common questions

PostgreSQL or MongoDB?

Can PostgreSQL handle our scale?

Explore further

Let’s talk about your PostgreSQL project