PostgreSQL + pgvector in Docker: A Complete Setup Guide

🐘 Installing and Deploying PostgreSQL + pgvector in Docker
This article shows how to quickly deploy a PostgreSQL database with the pgvector extension in a Docker Compose environment, so your local or development setup can support vector retrieval and AI applications (LangChain, RAG, semantic search, and the like).
📦 1. Prepare the Environment
Make sure your system has:
- Docker
- Docker Compose
- A
.envfile with database environment variables, for example:
POSTGRES_USER=postgres
POSTGRES_PASSWORD=postgres
POSTGRES_DB=appdb
🧱 2. Create the Project Structure
The recommended project layout:
dev-tools/
│
├── docker-compose.yml
├── .env
└── init.sql
⚙️ 3. Write the docker-compose.yml
Use the official pgvector/pgvector image (based on PostgreSQL 16/17, with the pgvector extension built in):
services:
postgre:
image: pgvector/pgvector:pg16
restart: always
healthcheck:
test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER} -d ${POSTGRES_DB}"]
interval: 10s
retries: 5
start_period: 30s
timeout: 10s
volumes:
- ./postgre:/var/lib/postgresql/data/pgdata
- ./init.sql:/docker-entrypoint-initdb.d/00_init.sql:ro
env_file:
- .env
ports:
- "5432:5432"
environment:
- PGDATA=/var/lib/postgresql/data/pgdata
- POSTGRES_PASSWORD=${POSTGRES_PASSWORD?Variable not set}
- POSTGRES_USER=${POSTGRES_USER?Variable not set}
- POSTGRES_DB=${POSTGRES_DB?Variable not set}
🗃️ 4. Initialize the pgvector Extension
Create the init.sql file:
-- Automatically enable the pgvector extension when the database initializes
CREATE EXTENSION IF NOT EXISTS vector;
This file runs automatically when the container first starts and the database initializes.
🚀 5. Start the Database
# Create the persistence directory (if it doesn't exist)
mkdir -p ./postgre
# Start the database service
docker compose up -d postgre
Check container status:
docker compose ps
When the status shows healthy, the database is up and running.
🔍 6. Verify pgvector Is Enabled
Run the following to confirm the extension exists:
docker compose exec -T postgre bash -lc \
'psql -U "$POSTGRES_USER" -d "$POSTGRES_DB" -c "SELECT extname, extversion FROM pg_extension WHERE extname='\''vector'\'';"'
Example output:
extname | extversion
---------+------------
vector | 0.8.0
(1 row)
🧠 7. A Quick Functional Test
Create a simple table in the database and run a vector similarity search:
docker compose exec -T postgre bash -lc '
psql -U "$POSTGRES_USER" -d "$POSTGRES_DB" <<EOF
CREATE TABLE items (id bigserial PRIMARY KEY, embedding vector(3));
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
SELECT id, embedding FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
EOF
'
Example output:
id | embedding
----+------------
1 | [1,2,3]
2 | [4,5,6]
(2 rows)
This confirms pgvector is enabled and can execute vector searches.
✅ 8. Summary
| Item | Value |
|---|---|
| Image | pgvector/pgvector:pg16 |
| Default port | 5432 |
| Data persistence directory | ./postgre |
| Initialization script | init.sql |
| Extension | pgvector |
With these steps you have successfully deployed PostgreSQL + pgvector in Docker. From here you can plug it straight into LangChain, LlamaIndex, or your own RAG application.
