Docker-Compose alongside AGE
Tags: apache, apacheage, bitnine, postgres
Published: 2023-05-07 07:52:53

Apache Age and PostgreSQL are two powerful tools that can be used to store, manage, and query data. In this article, we'll introduce you to these tools and show you how to install them on a macOS system using Docker Compose.

## Introduction to Apache Age and PostgreSQL

**PostgreSQL**

PostgreSQL is a powerful and feature-rich open-source relational database management system (RDBMS). It is known for its stability, reliability, and scalability, making it a popular choice for both small and large applications. PostgreSQL is often used for data warehousing, GIS applications, web applications, and more.

**Apache Age**

Apache Age is a graph database that is built on top of PostgreSQL. It allows users to store and query graph data using SQL queries. Apache Age is a great choice for applications that require graph data analysis, such as social networking, recommendation engines, and fraud detection.

**Installing Apache Age and PostgreSQL using Docker Compose**

To install Apache Age and PostgreSQL on a macOS system, we'll be using Docker Compose. Docker Compose is a tool that allows us to define and run multi-container Docker applications. With Docker Compose, we can define a YAML file that describes the services we want to run and their configuration. Let's get started!

**Step 1: Install Docker Desktop for macOS**
Before we can use Docker Compose, we need to install Docker Desktop for macOS. You can download it from the official Docker website.

**Step 2: Create a Docker Compose file**
Next, we'll create a Docker Compose file that describes the services we want to run. Create a new directory for your project and create a new file named docker-compose.yml with the following contents:

```
yaml
Copy code
version: '3'

services:
  db:
    image: postgres
    restart: always
    environment:
      POSTGRES_PASSWORD: password
      POSTGRES_USER: user
      POSTGRES_DB: mydatabase

  age:
    image: apache-age
    depends_on:
      - db
    environment:
      AGE_POSTGRES_HOST: db
      AGE_POSTGRES_PASSWORD: password
      AGE_POSTGRES_USER: user
      AGE_POSTGRES_DB: mydatabase
```

This Docker Compose file defines two services: db and age. The db service uses the official PostgreSQL image and sets some environment variables. The age service uses the Apache Age image and sets some environment variables that allow it to connect to the PostgreSQL database.

**Step 3: Start the containers**

Now we're ready to start the containers. Open a terminal and navigate to the directory where you saved the docker-compose.yml file. Run the following command:

`docker-compose up -d`

This command will start the containers in the background. You can use the -d flag to run them in detached mode. Wait for a few seconds while Docker pulls the necessary images and starts the containers.

**Step 4: Test the installation**

To test that everything is working correctly, we'll connect to the PostgreSQL database and create a test table. Open a new terminal window and run the following command to connect to the database:


`docker exec -it postgres psql -U user mydatabase`

This command connects to the mydatabase database using the user user. You'll be prompted to enter the password, which is password. Once you're connected, run the following SQL command to create a test table:


`CREATE TABLE test (id INT PRIMARY KEY, name VARCHAR(50));`

This command creates a table named test with two columns: id and name. You can now insert some data into the table and query it using SQL.

**Step 5:**

Congratulations! You have successfully installed Apache Age and PostgreSQL on your macOS system using Docker Compose. You can now use these tools to store, manage, and analyze graph data using SQL queries.

In this article, we introduced you to Apache Age and PostgreSQL and explained how to install them using Docker Compose on a macOS system. We hope you found this article helpful and that you're now ready to start exploring graph data with Apache Age and PostgreSQL.