PostgreSQL 16 · Supabase · pgvector

🐘 PostgreSQL
The database we trust most.

PostgreSQL is our primary database for nearly every project. We design schemas that last, write queries that perform, and build migration strategies that don't scare engineers.

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// PostgreSQL at Nexcode

// PostgreSQL expertise
version: "PostgreSQL 16 · Supabase · pgvector"
projects: 100+
rating: <10ms
delivery: "on-time & on-budget"

100+

PostgreSQL Databases

<10ms

Avg Query Latency

pgvector

AI/Embedding Expertise

Zero

Unplanned Downtime Events

Use Cases

What we build with PostgreSQL

Production applications we ship using PostgreSQL every day.

🏗

Application Databases

Primary data store for web and mobile apps — normalised schemas, proper indexes, migrations.

🔍

Full-Text & Vector Search

PostgreSQL's built-in FTS and pgvector for AI embedding storage and semantic search.

📊

Analytics Databases

Aggregations, window functions, and materialised views for reporting and analytics.

🔄

Event Sourcing

Append-only event tables with snapshot strategies for audit-trail and event-sourced systems.

⚡

High-Performance Queries

Query optimisation, explain plan analysis, and index strategies for sub-10ms queries.

☁

Managed PostgreSQL

RDS, Cloud SQL, Supabase, Neon — choosing and configuring managed services correctly.

Expertise Breakdown

Our PostgreSQL capabilities

📐

Schema Design

Normalisation & Modelling

✓ Schemas designed for correctness, performance, and future maintainability.

⚡

Query Optimisation

Performance Engineering

✓ EXPLAIN ANALYZE, index tuning, and query rewriting for 10x performance gains.

🔄

Migrations

Zero-Downtime Migrations

✓ Expand-contract pattern for schema changes that don't cause downtime.

🔍

pgvector

AI & Embedding Support

✓ pgvector for storing and querying OpenAI and custom embeddings.

📊

Analytics

Advanced SQL

✓ CTEs, window functions, and materialised views for complex analytics.

🔒

Security

Row-Level Security

✓ RLS policies for multi-tenant isolation and fine-grained access control.

Development Process

How we deliver PostgreSQL projects

01

📋

Requirements

02

📐

Schema Design

03

🔄

Migration Strategy

04

⚡

Performance Baseline

05

🔒

Security Setup

06

🔁

Backup & Recovery

07

📊

Monitoring

Ecosystem

The full PostgreSQL ecosystem we use

Core

→ PostgreSQL 16

→ pg_stat_statements

→ pg_audit

→ pgcrypto

Extensions

→ pgvector

→ PostGIS (geo)

→ pg_trgm (fuzzy search)

→ timescaledb

ORMs

→ Prisma

→ TypeORM

→ SQLAlchemy

→ Django ORM

Managed

→ AWS RDS

→ Supabase

→ Neon (serverless)

→ Cloud SQL

Pooling/Proxy

→ PgBouncer

→ pgpool-II

→ RDS Proxy

→ Supabase pooler

Migrations

→ Prisma Migrate

→ Flyway

→ Liquibase

→ Alembic

When to choose

PostgreSQL vs alternatives

An honest comparison to help you choose the right technology.

Feature	PostgreSQL	P	M	M
ACID Compliance	Full	Full	Full (v4+)	Limited
JSON Support	Excellent (jsonb)	Good	Native (document)	Native (document)
Full-Text Search	Built-in	Basic	Good	Limited
Vector Search	pgvector	Plugin only	Atlas Vector Search	Limited
Horizontal Scaling	Vertical + read replicas	Vertical + read replicas	Excellent sharding	Excellent
Best For	Most web apps, AI/ML data, analytics	Simple CRUD, PHP apps	Document-heavy, flexible schema	AWS-native, massive scale, key-value

FAQ

PostgreSQL
questions

Common PostgreSQL questions before you decide.

Start a Project →

PostgreSQL vs MySQL — which should we use?+

PostgreSQL for: complex queries, JSON/JSONB data, full-text search, vector search (pgvector), advanced data types, and strict SQL compliance. MySQL is fine for simple CRUD applications but PostgreSQL's feature set is objectively superior for most modern applications. We default to PostgreSQL.

How do you handle zero-downtime schema migrations?+

The expand-contract pattern: (1) add new column as nullable, (2) backfill with a batched background job, (3) add NOT NULL constraint, (4) remove old column after all code no longer references it. We never lock tables in production.

Can PostgreSQL handle our scale?+

PostgreSQL handles very high write volumes with proper connection pooling (PgBouncer), partitioning, and read replicas. Instagram ran on PostgreSQL for years. Supabase, Notion, and many unicorns still use PostgreSQL. If you're outgrowing PostgreSQL, you likely need CockroachDB or Spanner — not MongoDB.

What is pgvector and do we need it?+

pgvector is a PostgreSQL extension for storing and querying vector embeddings — the data format AI/LLM systems use for semantic search. If you're building RAG systems, semantic search, or anything that involves AI embeddings, pgvector lets you keep everything in one database without a separate vector store.

Related Tech

Often used with PostgreSQL

🟢

Node.js

Primary Node.js ORM is Prisma + PostgreSQL.

Explore →

⚛

React/Next.js

Full-stack with PostgreSQL via Prisma.

Explore →

🐍

Python

SQLAlchemy and Django ORM both love PostgreSQL.

Explore →

☁

AWS

RDS PostgreSQL on AWS.

Explore →

🐘 PostgreSQLThe database we trust most.

What we build with PostgreSQL

Our PostgreSQL capabilities

How we deliver PostgreSQL projects

The full PostgreSQL ecosystem we use

PostgreSQL vs alternatives

PostgreSQLquestions

Often used with PostgreSQL

Ready to build with PostgreSQL?

🐘 PostgreSQL
The database we trust most.

PostgreSQL
questions