rbehzadan/postgres

PostgreSQL for Data Science & AI Workloads 🧠📊

This Docker image provides PostgreSQL with powerful extensions optimized for data science, analytics, and AI/ML workloads.

🔥 Multi-Architecture Support: Available for AMD64 and ARM64 architectures.

📦 Features & Installed Extensions

This image comes with pre-installed PostgreSQL extensions for enhanced data processing, analytics, and AI use cases:

• 🔍 Vector search for AI/ML (pgvector)
• 📈 Time-series analysis (TimescaleDB)
• 📄 Parquet file format support (pg_parquet from CrunchyData)
• 📊 Graph database support (AGE)
• ⚡ Efficient JSON querying (jsquery)
• 🏗️ Partitioning for large datasets (pg_partman)
• 🛠️ Query optimization & hinting (pg-hint-plan)
• 🔒 Advanced auditing (pgaudit)
• 📅 Job scheduling inside PostgreSQL (pg_cron)
• 🔄 Event queueing system (pgq3)
• 🔡 Advanced regex support (pgpcre)

📌 Note: Building pg_parquet is resource-intensive and may take a long time.

🚀 How to Use This Image

1️⃣ Pull the Image

sh
docker pull rbehzadan/postgres:17.6

This automatically pulls the correct architecture (ARM64 or AMD64) based on your system.

2️⃣ Running the Container

sh
docker run -d --name postgres \
  -e POSTGRES_USER=admin \
  -e POSTGRES_PASSWORD=secret \
  -e POSTGRES_DB=mydb \
  -p 5432:5432 \
  rbehzadan/postgres:17.6

3️⃣ Connecting to the Database

Using psql:

sh
docker exec -it postgres psql -U admin -d mydb

🛠️ Enabling Extensions

Enable any installed extension inside PostgreSQL:

sql
CREATE EXTENSION pg_parquet;
CREATE EXTENSION timescaledb;
CREATE EXTENSION pgvector;
CREATE EXTENSION age;
CREATE EXTENSION pgq3;
CREATE EXTENSION pgpcre;

📊 Health Check

Verify the container's health status:

sh
docker inspect --format='{{json .State.Health}}' postgres

🖥️ Available Architectures

This image is available for the following architectures:
✅ AMD64 (linux/amd64)
✅ ARM64 (linux/arm64) (for ARM-based servers like AWS Graviton, Raspberry Pi, or Mac M1/M2 chips)

The correct version will be pulled automatically based on your system.

🤝 Contributing

If you find a bug, want to add an extension, or optimize the build process, feel free to:

• Report an issue on https://github.com/rbehzadan/postgres-docker
• Submit a pull request

📜 License

This project is licensed under the MIT License.

🎯 Why This Image?

This image is optimized for data science, AI, and large-scale analytics. Whether you're building a feature store for ML, processing time-series data, or handling graph-based queries, this setup provides high-performance PostgreSQL with the right extensions pre-installed.