Three Easy Steps to Install Docker PostgreSQL

One of the most important aspects of project development is managing project data, connecting it to apps, and many other things. Developers typically utilize DBMS to manage and store data, and PostgreSQL is a popular open-source relational option. PostgreSQL manages data through SQL queries and standards-based ACID guarantees for reliability.

Due to its flexibility and community support, PostgreSQL is included in the Docker platform as an official image. Docker provides operating-system level virtualization through containers, bundling apps with dependencies for simple deployment across environments.

This blog post will demonstrate three easy steps to install Docker PostgreSQL on Windows 10. We will also cover additional considerations for production PostgreSQL use in Docker environments.

How Containers Compare to Virtual Machines

Before diving into using Docker, it helps to understand how it compares to traditional virtualization. Solutions like VMware and VirtualBox run guest operating systems on virtualized hardware. This provides complete isolation for the VM instance but also comes with computational overhead.

By contrast, Docker containers share the host system kernel and hardware. Containers isolation is provided at the process level, wrapping apps in all required user space dependencies. This makes containers extremely lightweight versus VMs.

The Docker engine handles coordination between containers and the underlying OS. Developers build optimized container images containing only libs and settings needed to run the target application. This also minimizes disk usage and startup times compared to VMs.

In practice, a single server can run significantly more containerized app instances versus VMs. Containers also simplify replication across servers thanks to immutable infrastructure principles. Overall, containers excel for deploying microservices and distributed applications.

Benchmarking PostgreSQL on Docker

Numerous benchmarks demonstrate that PostgreSQL on Docker provides performance near native installations under multi-connection workloads. Docker imposes minimal overhead once running.

For example,hammerDB TPC-C testing shows Docker PostgreSQL at 97% the throughput of bare metal PostgreSQL on the same hardware. Performance is also consistent regardless of container counts thanks to native scheduling in the Linux kernel.

Resource utilization is similarly efficient. One benchmark configured jdmoore15/postgresql for handling 50 concurrent connections. This used only 11 MB of memory despite having availability for 414 connections.

In essence, Docker introduces negligible runtime overhead for PostgreSQL. Performance is close to metal while providing the deployment and management benefits of containerization.

Evaluating Different PostgreSQL Docker Images

The official postgres Docker Hub repository provides multiple tagged images to choose from. These are based on either Debian or Alpine Linux bases.

Debian Images

PostgreSQL Debian images range from version 9.6 to 14. The debian-10 tags utilize the latest Debian 10 Buster distribution. Image sizes range from 272 MB for latest to 319 MB for versioned 14 tags.

Alpine Images

Alpine is an extremely minimal distribution optimized for containers. Sizes range from 94 MB for latest to 104 MB for v14. However, some PostgreSQL extensions may not compile properly on musl libc.

The postgres Dockerfile builds either set of images. It establishes environment variables, locale settings, wired Tiger geolocation module, and initdb data population.

Additional Tagged Images

Many additional community images exist like:

• mdillon/postgis – PostgreSQL plus PostGIS and PostgreSQL extension geospatial data
• bitnami/postgresql – Production-optimized with authentication pluggable stacks
• dpage/pgadmin4 – Bundles pgAdmin4 for graphical admin

Evaluate options depending on your production vs local development use case requirements.

Connecting Other Languages and Frameworks

Thanks to ubiquitous PostgreSQL drivers and adapters, connecting various application stacks is straightforward. Here are some examples for languages like Python, Node.js and Java.

Python

The built-in psycopg Python module provides PostgreSQL integration and handling of types like arrays and UUIDs.

import psycopg2

conn = psycopg2.connect(
   host=container_ip,
   dbname=‘postgres‘, 
   user=‘postgres‘,
   password=‘mypassword‘
) 

cur = conn.cursor()
cur.execute(‘CREATE TABLE...‘)
conn.commit()

Node.js

JavaScript apps can utilize the community pg module. It supports connection pooling, transactions, prepared statements and more.

const { Pool } = require(‘pg‘)

const pool = new Pool({
  host: container_ip,
  database: ‘postgres‘,
  user: ‘postgres‘,
  password: ‘mypassword‘ 
})

pool.connect((err, client, release) => {
  // query logic  
})

Java

Native JDBC connectivity is provided via org.postgresql.Driver. This handles data types, query behavior and notifications.

Class.forName("org.postgresql.Driver");
Connection conn = DriverManager.getConnection(
    "jdbc:postgresql://container_ip:5432/postgres", "postgres", "mypassword"); 

Statement stmt = conn.createStatement();  
stmt.executeUpdate("CREATE TABLE..."); 

PostgreSQL containerization simplifies adoption across all your project‘s code.

Cloud Deployment of Containers

Once tested locally, Docker simplified deployment of containerized apps to production. All major cloud platforms now integrate Docker support.

For example, Amazon ECS, Google Cloud Run and Azure Container Instances (ACI) allow hosting containers directly. These auto-scale infrastructure needs based on demand.

Bespoke Docker cluster management is also available through:

• Amazon EKS
• Google GKE
• Azure AKS

These provide Kubernetes (K8s) orchestration layers. K8s helps operate container deployments at scale using desired state reconciliation.

Here is an example Kubernetes spec for deploying PostgreSQL:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: postgres 
spec:
  selector:
    matchLabels:
      app: postgres
  replicas: 3 
  template:
    metadata:
      labels:
        app: postgres
    spec:
      containers:
        - name: postgres
          image: postgres
          ports:
            - containerPort: 5432
          env:
            - name: POSTGRES_USER 
              value: "postgres"

This allows declarative PostgreSQL cluster management on K8s.

Persistent Storage and Data Considerations

Docker container storage utilizes the copy-on-write model. This means data volumes start ephemeral, getting wiped after restart by default.

That poses issues for stateful PostgreSQL requiring durable writes. Fortunately, named Docker volumes solve this:

docker run -d --name db 
    -v pgdata:/var/lib/postgresql/data 
    postgres

Now PostgreSQL will persist tables, indexes, and data to the pgdata host volume. This also facilitates data migrations across different containers.

For redundancy in distributed environments, remote durable volumes should be configured. Cloud block storage like S3, Azure Files or PD meet these needs.

Customizing the PostgreSQL Image

The PostgreSQL Dockerfile provides significant customization points for building tailored images.

Environment variables support adding extra .conf files into /usr/share/postgresql/ to override defaults. SQL init scripts configure specialized parameters.

One example is enabling WAL file compression for reduced disk usage:

FROM postgres
RUN echo "wal_compression = on" > /usr/share/postgresql/wal_compression.conf 

The Docker build process also allows injecting extra binaries, libraries like PostGIS, compiler flags, and customized pre-init steps.

Build optimizations such as multi-stage builds and distroless base images further minimize overhead. Combined with orchestrators managing replication, scaling and failover, production-grade PostgreSQL deployments are achievable.

Graphical Tools for Administering Containers

While the standard psql client suffices for developers, many prefer graphical database administration interfaces. The community dpage/pgadmin4container bundles the popular pgAdmin4 tool for this purpose.

The image sets up both pgAdmin web server and also a database to hold it‘s application data. Launching it linked to your PostgreSQL instance provides connectivity:

docker run -p 8080:80 \ 
    --link postgresdb:postgresdb \
    dpage/pgadmin4 

Now browse to the container IP on port 8080. Other tools like phpPgAdmin offer similar web-based PG management capabilities.

However, native desktop apps have challenges working inside containers. So developers may still prefer accessing central database servers from their local pgAdmin installs.

Recommended Practices for Security and Reliability

Since containers share kernels with the underlying host, hardening your Docker daemon is critical. AddingKernel capabilities like AppArmor on Linux reduce surface vulnerabilities.

Docker has shifted from insecure defaults like exposing containers on host IP stacks. But misconfigurations still risk exposing databases improperly. Never bind containers directly on host interfaces or standard ports.

Instead, place Docker deployments behind reverse proxies like Traefik or nginx. These terminate TLS connections directly so encryption keys remain on the edge servers. Route only necessary internal ports/protocols into containers.

Updating both host and container packages regularly is also imperative. Dynamic analysis tools like Clair and Anchore scan for CVEs across language stacks. Additionally, Kubernetes health checks validate running containers meet operational criteria.

Finally, following PostgreSQL best practices for user roles, connection limits, SSL and logical backup snaphots adds resiliency. The official image provides security and performance tuned for container infrastructure.

Conclusion

Installing Docker PostgreSQL only takes three easy platform-agnostic steps:

1. Install Docker Engine on your preferred OS or cloud server
2. Pull the official PostgreSQL image from Docker Hub
3. Run the container and access the PostgreSQL instance from other apps

As covered, Docker introduces minimal overhead for PostgreSQL while simplifying deployment and management. Containers facilitate replication and portability unavailable directly through VMs.

Combined with cloud infrastructure, Kubernetes orchestration, and ancillary tools like pgAdmin, PostgreSQL fits perfectly within modern container-driven architecture. Follow these steps and recommended production guidelines to harness Docker efficiently in your database infrastructure.