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What is PostgreSQL and how does it compare to other database management systems?

What is PostgreSQL?

PostgreSQL, also commonly referred to as Postgres, is an open-source, relational database management system (RDBMS). It is a popular database system that is also one of the best in terms of performance and scalability. Postgres is well-known for its feature-richness, flexibility and dependability, making it an excellent choice for a wide range of applications. Let’s take a closer look at Postgres and explore why it’s become such a popular choice for businesses and developers.
What is PostgreSQL?

How does Postgres compare to other database management systems?

The decision between Postgres and other databases will be determined by your organization's unique needs and requirements. Postgres is a strong choice for applications that require advanced query functionality, support for complex data structures, or the ability to handle large amounts of data. While you can find some details on how Postgres compares to other databases in the next question on applications and use cases, here are a few key ways in which Postgres compares to other databases:

Oracle vs Postgres
Oracle is a well-known enterprise-level RDBMS with a reputation for scalability and dependability. While Postgres adopted a procedural language name echoing Oracle’s (PL/SQL for Oracle and PL/pgSQL for Postgres), Postgres sets itself apart in terms of functionality, scalability, and licensing. For most use cases, Postgres is a capable and cost-effective alternative to Oracle, thanks to its reliability, flexibility, security, and active community support. Postgres is great for cost avoidance because it is open-source and has a lower total cost of ownership compared to Oracle.

MySQL vs Postgres
Like Postgres, MySQL is another popular open-source relational database management system. One key difference between the two is that MySQL uses a proprietary license, while Postgres uses a more permissive open-source license. Additionally, Postgres is generally considered to be more feature-rich and powerful than MySQL, particularly when it comes to handling complex queries and dealing with large amounts of data.

MongoDB vs Postgres
MongoDB is a NoSQL database management system designed to handle massive volumes of data in a flexible, JSON-like manner. It is generally easier to set up and use than Postgres but is not as feature-rich or powerful. It is also not as good at handling complex queries or transactions as Postgres.

Microsoft SQL Server vs Postgres
SQL Server, developed by Microsoft, supports a wide range of transaction processing, business intelligence, and analytics applications. It offers extensive integration with other Microsoft products, making it a preferred choice for many enterprises already invested in the Microsoft ecosystem (Microsoft Stack). While both SQL Server and Postgres are popular RDBMS options, SQL Server often has an edge in enterprise environments due to its comprehensive toolset, deep integration capabilities, and longstanding market presence, leading to its higher popularity in certain sectors.

Which applications and use cases are best suited for Postgres?

Postgres is a solid choice for many different applications. Some of the scenarios where it works best are:

Data warehousing and business intelligence
Postgres has powerful built-in support for advanced analytics and data warehousing, making it well-suited for use cases such as data mining, business intelligence, and reporting.

Content management and E-commerce
The native JSON support and full-text search capabilities of Postgres make it well-suited for content management and e-commerce applications.

Geographic information systems (GIS)
Postgres includes built-in support for geographic data and spatial indexing, is well recognized as a great choice for geographic information systems (GIS) and location-based services.

Web and mobile applications
Postgres is a popular choice for web and mobile app development, thanks to its scalability, robustness, and support for advanced features such as full-text search and JSON data types.

Gaming and social media
Postgres can handle high-traffic and high-concurrency which makes it well-suited for gaming and social media applications.

DevOps and cloud-native
Postgres is well-suited for cloud-native deployment and DevOps, integrating smoothly with modern CI/CD pipelines and cloud services. In the context of service-oriented architectures like microservices, Postgres becomes even more relevant. With containerization, especially using platforms like Kubernetes, Postgres can be efficiently managed, making it a strong choice for microservices in cloud-native environments.

Internet of things (IoT)
Postgres can handle large amounts of data and process complex queries make it well-suited for IoT applications.

Financial and government
Compliance with regulations and data integrity features makes Postgres well-suited for financial and government applications.

What are the key features of Postgres?

While Postgres has a multitude of powerful capabilities, here are some of the most popular features:

Postgres is an ORDBMS

Postgres is often categorized as an ORDBMS (Object-Relational Database Management System) due to its ability to handle complex data types and store and retrieve objects. In comparison to traditional RDBMS (Relational Database Management System), ORDBMSs are better suited to handling complex data structures and have more advanced query capabilities.

In the context of NoSQL databases, which are designed to handle large amounts of unstructured or semi-structured data, ORDBMSs like Postgres have some advantages over traditional RDBMSs. NoSQL databases often prioritize scalability, availability, and high-speed data access over data consistency, whereas ORDBMSs are designed to prioritize data consistency while still providing some flexibility in data modeling.

The Postgres support for JSON and other semi-structured data types make it a viable option for applications that require some NoSQL capabilities. Additionally, Postgres's extensibility allows developers to add custom data types, functions, and operators, providing flexibility in data modeling and query capabilities. Postgres also has strong support for indexing, allowing for efficient retrieval of data even when dealing with large and complex data structures.

Foreign Data Wrappers
Foreign Data Wrappers (FDWs) in Postgres are beneficial for several reasons:

  • Data integration: FDWs allow you to integrate data from multiple sources into a single database, without having to physically move the data or create duplicate copies of it. This makes it easier to access and analyze data from disparate sources.
  • Performance: With FDWs, you can query data from external sources directly from within Postgres, without having to first extract and load the data. This can significantly improve query performance, especially when dealing with large datasets.
  • Data federation: FDWs allow you to create a unified view of data from multiple sources, even if the data is stored in different formats or on different platforms. This can simplify data analysis and reporting, and can also help to avoid data silos.
  • Data virtualization: FDWs allow you to create virtual tables in Postgres that are backed by data in external sources. This means that you can query external data as if it were stored locally in Postgres, without having to first load it into Postgres. This can simplify application development and reduce data redundancy.

Overall, FDWs in Postgres provide a powerful and flexible mechanism for integrating, analyzing, and reporting on data from multiple sources.

ACID compliance
Postgres has the four properties of ACID compliance (atomicity, consistency, isolation, and durability) to make sure that database transactions are handled reliably.

The database supports a wide range of data types and can be easily extended with custom functions, operators, and aggregates.

High performance
Postgres is known for its high performance, especially when handling large amounts of data and complex queries.

SQL compliance
Postgres is compliant with the SQL standard which ensures it is easy to use for developers and analysts familiar with SQL.

Concurrency control
Postgres offers multi-version concurrency control (MVCC), which enables concurrent access to the same data by several transactions without conflicts.

Advanced indexing
Postgres supports various index types, including B-trees, Hash, GiST, SP-GiST, and GIN.

Replication and high availability
Postgres supports both synchronous and asynchronous replication and provides several tools for achieving high availability.

Advanced security
Postgres features role-based access control, data encryption, and connection security.

Data warehousing and business intelligence
Well suited for data warehousing and business intelligence tasks, Postgres supports advanced analytics and data visualization.

Community-driven development
Postgres is an open-source project with a large, active community, which contributes to the development and maintenance of the database.

Why are companies increasingly adopting Postgres?

Postgres an attractive alternative to other databases for many organizations, especially as more and more companies are moving to the cloud and looking for more cost-effective and flexible solutions. Some of the key reasons for the increase in adoption include:

Cost effectiveness
Postgres is open-source software, which means it has no licensing costs and a lower total cost of ownership compared to proprietary databases.

High scalability
Postgres offers horizontal scalability with read replicas and connection pooling, which make it a good fit for high-traffic and high-concurrency applications.

Postgres is more flexible and can be easily customized to meet specific needs, it also supports a wide variety of operating systems, hardware platforms, and programming languages.

Strong community
Postgres has a large and active community of users and developers, making it easier to find support and resources.

Advanced features
Postgres has many advanced features such as native JSON support, full-text search, and better performance for complex queries.

Postgres has a more cloud-friendly architecture and is better suited for modern cloud-based deployments.

Open-source licensing
The open-source license of Postgres allows for greater flexibility and freedom in terms of modifying and distributing the software.

High performance
Postgres is well known for its high performance, allowing it to handle large amounts of data.

Are there any potential concerns for adopting Postgres?

Like any software, Postgres has its own set of concerns and limitations. Below are some of the common concerns with adopting and using Postgres. It's worth noting that many of these can be addressed by having experienced database administrators (DBAs) and developers on your team, as well as utilizing third-party tools and services to address any gaps in the functionality of Postgres.

Postgres can be complex for new users to set up and use. It has a large set of features and options, which can make it overwhelming for beginners.

While Postgres can scale well, it can be challenging to manage for large-scale applications. Database administrators need to have experience with advanced database administration tasks such as replication, clustering, and partitioning.

Postgres can be slower compared to some other database systems, especially for write-intensive applications. However, it has many features and configuration options that can be tuned to improve performance.

The documentation for Postgres can be difficult to navigate, especially for users unfamiliar with database terminology.

Lack of built-in tools
Compared to some other database systems, Postgres does not have built-in tools for backups, monitoring and management. However, there are many third-party tools available that can provide these features.

Migrating from other databases to Postgres can be a challenge, especially if you're dealing with large volumes of data.

While Postgres is open-source and free to use, some third-party tools and support services do come with a cost.

How should you plan for adopting Postgres?

According to DB-Engines, there are 422 distinct database management systems available. This scale of choice enables developers to match databases to specific workloads. However, the proliferation of platforms increases the technological width for operations to support. Eventually, consolidation will be necessary for manageable support in the long-term.
From a policy perspective, management should be restricting the choice of platform for developers to choose from but if the wrong short list of technology is chosen, then performance could be impacted. The scale of impact depends on the scenario. Either way, developers want a choice of platform to suit their needs and management needs to keep tight control on the technology choices they’ll be expected to support for many years to come. 

That shortlist of technology should have a mix of database platforms with the resources trained to support them and not just stick with traditional relational database management systems. This is why we advocate to have Postgres as an option, as a minimum, for development teams to choose as a database for their applications. 

When planning to adopt Postgres in your organization, you should consider the following key steps:

Assess current database needs
Determine the current and future needs of your company databases, such as data volume, number of users, and required performance levels.

Evaluate the capabilities of Postgres
Research the capabilities and features of Postgres to ensure they meet the company's needs.

Plan for migration 
Develop a plan for migrating existing data to Postgres and for updating any existing applications to use it. During the discovery phase, you’ll need to weigh the costs of Retiring, Retaining, Rehosting, Replatforming, Refactoring, and Re-architecting. If you are either Re-architecting, Re-hosting, Re-platforming, or Re-factoring, you will need to migrate data. A Blue/Green deployment is one method to derisk a cutover in a migration. 

Before the actual migration, conduct an assessment of your current database. Identify the size, type of data, interdependencies, and potential challenges for migration.

Data Preparation
Cleanse and prepare your data for migration. This involves removing any redundant data, ensuring data consistency, and transforming data to the target schema if necessary.

Create or update documentation to reflect changes. This includes system documentation, user manuals, and operational procedures.

Migration Execution
Use tools or scripts to move data from the source to the target (Postgres). Ensure data integrity and completeness after the migration.

Pilot Migration
Perform a small-scale pilot migration to identify potential issues and fix them before the full-scale migration.

Rollback Plan
Have a plan in place to revert to the original state if the migration encounters significant issues. For mission-critical systems where no downtime is a requirement, we recommend setting up bi-directional replication between the source and the target databases. This is now facilitated by SharePlex by Quest for Oracle to Oracle or Oracle to Postgres deployments. 

Backup and recovery
Ensure the proper backup and recovery plan and process is in place.

Monitor and maintain
Monitor the performance and stability of the Postgres database and implement regular maintenance and updates as needed.

Performance Tuning
Over time, optimize the Postgres database for better performance based on usage patterns.

Ensure that your team is well-trained on the new platform. This involves both technical training (for IT staff) and user training (for end-users).

Get help
Consider hiring experts or getting support from a company that specializes in Postgres.

Feedback Loop
Establish a mechanism to collect feedback from end-users post-migration. Use this feedback to make necessary adjustments.

Where can I get help for fully leveraging Postgres?

Quest® offers an extensive portfolio of solutions for moving, managing and monitoring Postgres environments. We can help you properly model, migrate, manage, monitor, govern and protect your data and application ecosystem. Here’s where you can learn more.

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