Complete guide to PostgreSQL: Features, use cases, and tutorial

What Is PostgreSQL?

PostgreSQL is an open source relational database management system. Known for its reliability, it supports both SQL and JSON querying. Its adherence to standards and extendable nature makes it a popular choice for various applications, ranging from web applications to data warehousing.

The system provides data integrity and reliability. It features ACID compliance, ensuring that in the event of a crash, the database maintains consistency. Additionally, PostgreSQL supports various data types and performance optimization features.

The history of PostgreSQL

PostgreSQL has its roots in the POSTGRES project at the University of California, Berkeley, initiated by Professor Michael Stonebraker in 1986. The project aimed to overcome the limitations of existing relational database systems by adding support for complex data types and more flexible query capabilities.

The original system, POSTGRES, introduced several innovative features, such as the ability to define types, operators, and methods. In 1996, the project was renamed to PostgreSQL to emphasize its support for SQL, the industry-standard query language. This marked its evolution into a relational database management system (RDBMS).

The adoption of the SQL standard made PostgreSQL more accessible to a broader range of developers and applications, contributing to its popularity. PostgreSQL has continued to evolve, driven by an open source community. Key features introduced include multi-version concurrency control (MVCC), point-in-time recovery, and support for non-relational data types like JSON.

Key features of PostgreSQL database

The database offers the following capabilities:

Custom data types: Enables developers to define new data types based on their application requirements, extending the database’s functionality. These improve compatibility and ensure that the database schema aligns with the application’s data representation needs. Examples include composite types and enumerated types.
Procedural languages: Its support for languages like PL/pgSQL allows developers to create complex functions and operations within the database. This extends the database’s functionality beyond SQL queries, enabling more extensive data processing and manipulation. By encapsulating complex logic in stored procedures, developers can maintain cleaner and more manageable codebases
Constraints and triggers: Constraints enforce rules on data columns, ensuring integrity and accuracy. Types such as primary keys, foreign keys, and unique constraints maintain data relationships, preventing inconsistent entries. Triggers automate tasks in response to database events, such as insertions or updates. They execute programmed functions whenever specified actions occur.
Advanced indexing: Supports various index types, including B-tree, Hash, GIN, and GiST, catering to different data operations and query types. These provide efficient data retrieval in complex query scenarios, minimizing search time and improving application responsiveness. With partial indexing, developers can create indexes on subsets of data.
Full-text search: Allows for efficient, text-based data querying. This enables the searching, filtering, and ranking of plain text data, useful for applications handling large volumes of text, such as search engines or document repositories. It supports complex search requirements like stemming, stop words, and ranking based on relevance.
Replication and high availability: With streaming replication, changes are continuously sent from the master to the standby server, ensuring uptime and data integrity. Logical replication allows selective data set replication and bi-directional replication setups. These capabilities enable flexible deployment architectures, ensuring that databases remain available and responsive under heavy loads or in case of failures.

Tips from the expert

Sharath Punreddy

Solution Architect

Sharath Punreddy is a Solutions Enginee with extensive experience in cloud engineering and a proven track record in optimizing infrastructure for enterprise clients

In my experience, here are some advanced tips that can make better use of PostgreSQL:

Understand query execution plans (EXPLAIN/ANALYZE): Regularly use the EXPLAIN and ANALYZE commands to understand how your queries are being executed. This helps identify bottlenecks such as unnecessary full table scans, and optimize queries by adding the right indexes or restructuring joins.
Optimize indexing with covering indexes: PostgreSQL allows the creation of covering indexes, where the index includes all the columns needed to resolve a query. This avoids fetching rows from the heap and can significantly speed up read performance.
Leverage parallel query execution: PostgreSQL supports parallel query execution for large data sets. Ensure your queries are taking advantage of this by configuring parameters like max_parallel_workers_per_gather and analyzing queries for parallelizable parts, especially for analytical workloads.
Monitor for index bloat: Over time, indexes can become bloated due to frequent updates and deletes. Use tools like pgstattuple or pg_repack to detect and remove index bloat, ensuring indexes remain performant and don’t consume unnecessary disk space.
Carefully tune autovacuum settings: Autovacuum is critical for maintaining performance by cleaning up dead tuples, but its default settings can be suboptimal. Adjust parameters like autovacuum_vacuum_threshold, autovacuum_naptime, and autovacuum_vacuum_scale_factor based on your workload to prevent table bloat and performance degradation.

Benefits of using PostgreSQL

There are several reasons to use PostgreSQL.

Standards compliance

PostgreSQL is known for its standards compliance, sticking closely to SQL standards while providing extensive features. It covers core functionalities like foreign keys, joins, views, triggers, and stored procedures. This compatibility ensures PostgreSQL can be easily integrated with various applications and technologies.

Performance and scalability

PostgreSQL can manage complex queries and indexing, increasing data retrieval speeds. Performance tuning options and optimization tools enable fine-tuning for workload requirements and environments. PostgreSQL also supports growing data needs through features like table partitioning and replication.

Learn more in our detailed guide to Postgres management (coming soon)

Cross-platform compatibility

PostgreSQL allows deployment across different operating environments, including Linux, Windows, and macOS. It can integrate smoothly into heterogeneous IT environments, simplifying setup and reducing system interdependencies. This supports a range of applications, from desktop to cloud-based solutions.

Open source license and community

PostgreSQL’s open source license encourages community collaboration and continuous improvement. This community-driven development ensures a feature-rich and stable database system that evolves with user needs. Access to the source code means developers can modify PostgreSQL to tailor functionalities.

Common use cases of PostgreSQL

Here are some of the main use cases for PostgreSQL.

Data warehousing and analytics

PostgreSQL is well-suited for data warehousing and analytics, offering querying and integration with analytical tools. It efficiently handles medium to large data sets, enabling organizations to derive insights and trends for strategic decision-making. It can be used to conduct deep analytics and generate comprehensive reports.

Web applications

Its stability, scalability, and performance handle dynamic web platforms, processing numerous transactions and user requests. The database’s support for JSON allows integration with modern web technologies, increasing development flexibility. Its compatibility with various programming languages and frameworks enables quick setup and management.

Geographic information systems

PostgreSQL, especially with the PostGIS extension, supports geographic information systems (GIS). This enables the handling of spatial data, crucial for applications like mapping, spatial analysis, and geolocation services. Users can perform complex spatial queries and modeling tasks, useful for urban planning and logistics.

Database consolidation

PostgreSQL offers a unified platform for managing diverse data types and systems. It simplifies data management by consolidating multiple databases into a single, cohesive system, reducing complexity and operational overhead. This promotes data consistency and integrity.

Telecommunications

In telecommunications, PostgreSQL provides reliable, high-performance solutions for managing large data volumes and complex transactions. Its scalability and concurrency features ensure efficient handling of daily operations, including billing, customer data management, and network resource monitoring.

PostgreSQL vs. Other databases

Here are comparisons between PostgreSQL and popular alternatives.

PostgreSQL vs MySQL

PostgreSQL offers more functionalities such as support for complex queries, data integrity, and extensibility, making it suitable for applications requiring comprehensive data operations and strong performance.

MySQL emphasizes simplicity and speed, often seen in web applications with less complex demands. Its ease of use and widespread support make it suitable for simpler applications. Like PostgreSQL, it is also an open source relational database.

Learn more in our detailed guide to PostgreSQL vs MySQL

PostgreSQL vs MongoDB

MongoDB contrasts with PostgreSQL’s relational approach. It is useful for handling unstructured data formats such as JSON and is well-suited for rapid development cycles with schema-free designs. It caters to use cases where scalability and flexibility in data modeling are prioritized over transactional integrity.

PostgreSQL offers ACID compliance, ensuring data consistency across transactions. Its ability to handle both relational and some NoSQL features via JSON support makes it a versatile choice for applications requiring structured and semi-structured data handling.

Learn more in our detailed guide to Postgres vs MongoDB (coming soon)

PostgreSQL vs MariaDB

PostgreSQL is known for extensibility and features such as window functions and complex queries. It has greater transaction support and adherence to SQL standards.

MariaDB, derived from MySQL, focuses on enhanced storage engines and quick replication features, making it suitable for applications prioritizing speed over complexity. Its focus on speed and high performance for simple operations can be advantageous for applications requiring rapid data handling with fewer advanced transactional needs.

Learn more in our detailed guide to Postgres vs MariaDB (coming soon)

PostgreSQL vs MSSQL

Microsoft SQL Server (MSSQL), developed by Microsoft, offers deep integration with Windows and enterprise-level features but comes with licensing costs. It is most appropriate in enterprise environments heavily embedded with Microsoft technologies. MSSQL is commercial software which can present significant license fees for large scale deployments.

PostgreSQL, as an open source database, provides similar capabilities such as complex queries and indexing without the license cost of MSSQL. Both databases provide strong ACID compliance, but PostgreSQL’s flexibility in deployment across platforms like Linux and macOS stands out. PostgreSQL offers more deployment versatility and customization in diverse environments.

Learn more in our detailed guide to Postgres vs MSSQL (coming soon)

Tutorial: Getting started with PostgreSQL

This tutorial guides you through the process of installing PostgreSQL on Windows and Ubuntu, and then connecting to a database server.

Installing PostgreSQL on Windows

To install PostgreSQL on Windows, follow these steps:

Begin by navigating to the EnterpriseDB download page and selecting the latest version of PostgreSQL for Windows, such as version 16.1.
Choose the x86-64 architecture, which is suitable for most modern systems. The download process will take a few minutes.
Once the download is complete, double-click the installer file. The PostgreSQL installation wizard will launch, guiding you through the setup process. Click Next on the welcome screen.
Choose the installation directory. You can either accept the default location or specify a different directory based on your preference, then click Next.
Select the components you want to install. The available options include:
- PostgreSQL server: Installs the PostgreSQL database server.
- pgAdmin 4: Installs the graphical user interface management tool for PostgreSQL.
- Command line tools: Installs tools like psql and pg_restore for command-line interaction with the database.
- Stack Builder: Assists in downloading and installing additional drivers and tools. This can be skipped for now.
After selecting the necessary components, click Next.
Now to configure the database directory and credentials. Choose the directory for storing the database data. You can accept the default or specify a different directory.
Set a password for the PostgreSQL superuser (commonly postgres). Retype the password to confirm, and then click Next.
Specify the port number for PostgreSQL to listen on, typically 5432, ensuring no other applications use this port.
Select the default locale for the PostgreSQL server. Leaving it as the operating system default is generally sufficient.
Review the installation summary. If everything is correct, click Next to start the installation. The process may take a few minutes.
After installation is complete, click the Finish button.

Adding PostgreSQL to the System PATH

To ensure you can use PostgreSQL’s command-line tools from any directory, you need to add the PostgreSQL bin directory to your system’s PATH environment variable:

Locate the bin directory, usually found in C:\Program Files\PostgreSQL\\bin.
Press Win and R, then type sysdm.cpl, and press Enter to open the System Properties dialog.
Go to the Advanced tab and click on Environment Variables.
Under User variables or System variables, select the Path variable and click Edit.
Click New, enter the path to the PostgreSQL bin directory, and click OK.
Close all dialog boxes by clicking OK. PostgreSQL is now installed and configured on your Windows system, ready for use.

Installing PostgreSQL on Ubuntu

To install PostgreSQL on Ubuntu, follow these steps:

First, ensure your package index is up to date and install the necessary packages:

sudo apt update sudo apt install gnupg2 wget

1
2

sudo apt update
sudo apt install gnupg2 wget
Next, add the PostgreSQL repository to your system:

sudo sh -c 'echo "deb http://apt.postgresql.org/pub/repos/apt $(lsb_release -cs)-pgdg main" > /etc/apt/sources.list.d/pgdg.list'

1

sudo sh -c 'echo "deb http://apt.postgresql.org/pub/repos/apt $(lsb_release -cs)-pgdg main" > /etc/apt/sources.list.d/pgdg.list'
Then, import the repository signing key:

curl -fsSL https://www.postgresql.org/media/keys/ACCC4CF8.asc | sudo gpg --dearmor -o /etc/apt/trusted.gpg.d/postgresql.gpg

1

curl -fsSL https://www.postgresql.org/media/keys/ACCC4CF8.asc | sudo gpg --dearmor -o /etc/apt/trusted.gpg.d/postgresql.gpg
Update your package list again to include the new PostgreSQL repository:

sudo apt update

1

sudo apt update
To install PostgreSQL 16 along with its additional modules, run the following command:

sudo apt install postgresql-16 postgresql-contrib-16

1

sudo apt install postgresql-16 postgresql-contrib-16
After installation, start the PostgreSQL service:

sudo systemctl start postgresql

1

sudo systemctl start postgresql
To ensure PostgreSQL starts automatically on boot, enable the service:

sudo systemctl enable postgresql

1

sudo systemctl enable postgresql
PostgreSQL stores its configuration files in the postgresql.conf file. You can edit this file using a text editor like nano:

sudo nano /etc/postgresql/16/main/postgresql.conf

1

sudo nano /etc/postgresql/16/main/postgresql.conf
If you want to allow remote connections, set listen_addresses to *:

listen_addresses = '*'

1

listen_addresses = '*'

Next, configure PostgreSQL to use MD5 password authentication by modifying the pg_hba.conf file. This is important if you plan to enable remote connections:

sudo sed -i '/^host/s/ident/md5/' /etc/postgresql/16/main/pg_hba.conf
sudo sed -i '/^local/s/peer/trust/' /etc/postgresql/16/main/pg_hba.conf
echo "host all all 0.0.0.0/0 md5" | sudo tee -a /etc/postgresql/16/main/pg_hba.conf

1

2

3

sudo sed -i '/^host/s/ident/md5/' /etc/postgresql/16/main/pg_hba.conf

sudo sed -i '/^local/s/peer/trust/' /etc/postgresql/16/main/pg_hba.conf

echo "host all all 0.0.0.0/0 md5" | sudo tee -a /etc/postgresql/16/main/pg_hba.conf

Restart PostgreSQL to apply the changes:

sudo systemctl restart postgresql

1

sudo systemctl restart postgresql
If your system uses a firewall, allow traffic on PostgreSQL’s default port (5432) with:

sudo ufw allow 5432/tcp

1

sudo ufw allow 5432/tcp

Connecting to a PostgreSQL database server

Connecting to a PostgreSQL database server can be done through several tools, each offering unique advantages depending on the task at hand. Below, we’ll guide you through connecting using both the psql terminal-based utility and the pgAdmin graphical interface.

The psql tool is a command-line interface for interacting directly with the PostgreSQL server. It allows you to execute SQL commands, manage database objects, and perform various administrative tasks. pgAdmin is a web-based interface that simplifies database management with a graphical interface. It’s suitable for those who prefer not to work from the command line.

Steps to connect using psql:

On Windows, open the Command Prompt. On Unix-like systems (Linux, macOS), open Terminal.
Use the following command to connect to the PostgreSQL server:

psql -U postgres

1

psql -U postgres

<olclass=”component-list”>
psql<c/ode>: This invokes the psql program.
-U postgres: This specifies the PostgreSQL user you are logging in as. The -U option must be uppercase.

After running the command, you will be prompted to enter the password for the postgres user:

Password for user postgres: mypassword

1

Password for user postgres: mypassword
If the credentials are correct, you will be connected, and the prompt will change to something like this:

postgres=#

1

postgres=#
To verify the connection, you can check the PostgreSQL version by running:

SELECT version();

1

SELECT version();
The output will display the PostgreSQL version, confirming the successful connection to the database server
You can also check the current database with:

SELECT current_database();

1

SELECT current_database();
And the server’s IP address and port with:

SELECT inet_server_addr(), inet_server_port();

1

SELECT inet_server_addr(), inet_server_port();

Steps to Connect Using pgAdmin:

Open pgAdmin from the Start menu or your applications list. It will launch in your default web browser.
Right-click on the Servers node in the left-hand panel and select Register, then Server.
In the dialog box, enter a name for the server connection (e.g., “Local”).
In the Connection tab, enter the host (usually localhost) and the password for the postgres user.
Click the Save button to establish the connection and save the configuration.
Expand the Servers node, and you will see the connected PostgreSQL instance with the default postgres database.
To run SQL queries, select Tool, then Query Tool from the menu. Enter your SQL commands in the editor, and click the Execute button to run them. The results will be displayed in the Data Output tab.

Learn more in our detailed guide to PostgreSQL tutorial (coming soon)

PostgreSQL best practices

Developers and administrators can use the following practices to ensure the most effective use of the PostgreSQL database.

Normalize data appropriately

Normalization helps ensure efficient data management and avoid redundancy. It involves organizing the database into tables and columns that minimize duplicate data. Proper normalization typically follows the principles of the first, second, and third normal forms, ensuring that each table represents a single subject, and relationships between tables are properly established using foreign keys.

However, while normalization improves data integrity and reduces storage costs, over-normalization can lead to performance bottlenecks due to complex joins. It’s essential to find a balance that maintains data integrity without sacrificing query performance. In some cases, denormalization might be needed, particularly in read-heavy environments.

Use proper data types

Selecting the appropriate data types in PostgreSQL is essential for both performance and storage efficiency. PostgreSQL offers a range of data types, including standard types like integers and text, as well as more advanced types like JSON, arrays, and custom data types.

Using the correct data type ensures that the database uses storage efficiently and processes queries faster. For example, using INT instead of BIGINT when possible saves space and speeds up operations. PostgreSQL’s advanced data types include UUID for unique identifiers and JSONB for storing and querying JSON data.

Implement performance tuning

Optimizing PostgreSQL performance involves several strategies, including query optimization, index management, and configuration tuning. Regularly analyze query execution plans using EXPLAIN to identify slow queries and improve them by rewriting the query or adding appropriate indexes.

Memory configuration parameters such as shared_buffers, work_mem, and maintenance_work_mem should be tuned according to the system’s resources and workload. Additionally, adjusting autovacuum settings can help manage table bloat, maintaining the database’s performance over time.

Learn more in our detailed guide to Postgres tuning (coming soon)

Leverage replication and clustering

PostgreSQL supports various replication methods, including streaming replication and logical replication, to improve data availability and reliability. Streaming replication creates a hot standby server that mirrors the primary server in real time, providing high availability and enabling failover in case of a primary server failure.

Clustering with solutions like Patroni or Postgres-XL can distribute the database load across multiple nodes, improving scalability and fault tolerance. When setting up replication or clustering, ensure that network latency and resource allocation are optimized to prevent replication lag and ensure smooth failover processes.

Learn more in our detailed guide to Postgres cluster (coming soon)

Implement partitioning and sharding

Partitioning large tables in PostgreSQL can improve query performance and manageability. PostgreSQL supports declarative partitioning, allowing tables to be divided into smaller, more manageable pieces (partitions) based on a key such as date or range. This reduces the amount of data scanned in queries, leading to faster query execution.

Sharding, or horizontal partitioning, involves distributing data across multiple servers or databases to handle large-scale applications. This can improve performance and scalability, particularly in systems that require high transaction throughput or large amounts of data storage.

Establish backup and recovery strategies

Regular backups are essential for data safety in PostgreSQL. Use tools like pg_dump for logical backups or pg_basebackup for physical backups to create consistent database snapshots. For large databases, consider using continuous archiving with PITR (Point-In-Time Recovery) to recover the database to any given time.

It’s important to regularly test backup and recovery procedures to ensure they work as expected in case of a disaster. Automating backup processes and monitoring them for successful completion can prevent data loss and minimize downtime in the event of a failure.

Learn more in our detailed guide to Postgres best practices (coming soon)

The benefits of Instaclustr for PostgreSQL databases

Instaclustr offers a host of benefits specifically tailored for PostgreSQL databases, making it an ideal solution for organizations seeking efficient and reliable management of their PostgreSQL deployments. With its managed services approach, Instaclustr simplifies the deployment, configuration, and maintenance of PostgreSQL databases, freeing up valuable resources and enabling businesses to focus on their core applications and data-driven insights.

Some of the benefits of Instaclustr for PostgreSQL include:

Comprehensive managed services infrastructure management, provisioning, configuration, and security, ensuring that organizations can leverage the power of this robust relational database management system without the complexities of managing it internally. By offloading these operational tasks to Instaclustr, organizations can reduce the burden on their internal teams and ensure that their PostgreSQL databases are managed effectively and securely.
Automated scaling capabilities, enabling PostgreSQL to seamlessly handle increasing workloads by adding or removing resources as needed. This ensures that applications relying on PostgreSQL can accommodate spikes in traffic and scale to meet future growth demands. Instaclustr’s platform actively monitors the health of the database cluster, automatically handling scaling processes to ensure optimal resource utilization and cost efficiency.
High availability and fault tolerance for PostgreSQL databases. By employing replication and failover mechanisms, Instaclustr ensures that data is stored redundantly across multiple nodes in the cluster, providing resilience against hardware failures and enabling continuous availability of data. Instaclustr’s platform actively monitors the health of the database cluster and automatically handles failover and recovery processes, minimizing downtime and maximizing data availability for PostgreSQL deployments.

Furthermore, Instaclustr’s expertise and support are invaluable for PostgreSQL databases. Our team of experts has deep knowledge and experience in managing and optimizing PostgreSQL deployments. We stay up-to-date with the latest advancements in PostgreSQL technologies, ensuring that the platform is compatible with the latest versions and providing customers with access to the latest features and improvements. Instaclustr’s 24/7 support ensures that organizations have the assistance they need to address any PostgreSQL-related challenges promptly.

For more information see: