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PostgreSQL vs. MySQL: Choosing the Right Database for Your Project

Explore the key differences and similarities between PostgreSQL and MySQL to find the best database solution for your project's needs.
Updated Sep 20, 2024  · 8 min read

Relational databases have been around for a long time. In fact, relational database management systems (RDBMS) were on the front lines during the dawn of data warehousing and held their ground during the data science revolution. Even in the age of AI and LLM’s, relational databases are at the heart of almost every enterprise’s data ecosystem.

Relational databases store data in a “rectangular” manner; tables are made up of columns and rows and are organized in databases. Relational databases leverage SQL (structured query language) to store, manage, and retrieve data.

With an ever-growing number of tools in the data space, choosing the right one is more important than ever. Sophisticated features and functionality in the latest and greatest technology offerings have spawned a new tradeoff: finding a solution that meets the requirements for the use case at hand while ensuring that performance and costs are tolerable.

Together, we’ll explore PostgreSQL and MySQL, their similarities and differences, and the most important things to remember when choosing a relational database management system to tackle your next project.

PostgreSQL vs. MySQL: An Overview

Let’s start with some quick definitions of PostgreSQL and MySQL so that we can familiarize ourselves with these two relational database management systems.

What is PostgreSQL?

PostgreSQL, or Postgres, is a relational database management system (RDBMS) commonly used to store and retrieve tabular data organized in databases and tables. The RDBMS is one of the most widely used in industry due to its extensible framework and reliability. Postgres is an open-source tool that is free to download and use. Postgres is compatible with all major operating systems and supports a number of extensions and plugins. In addition to being a tool to store data, Postgres offers a flavor of SQL to interact with and manage the data it persists.

For more information about getting started with Postgres, check out the Beginner’s Guide to PostgreSQL.

What is MySQL?

Like Postgres, MySQL is an RDBMS that leverages databases and tables to organize, store, and retrieve tabular data. MySQL is also open source, although heavily supported by Oracle. While MySQL boasts broad functionality, it offers fewer features than Postgres, helping to make it a more “lightweight” tool.

MySQL is most commonly used when building web applications, and like Postgres, it implements its own twist on SQL to manage and query data. This MySQL Tutorial offers a comprehensive guide for beginners to get started with MySQL with a number of hands-on exercises and examples.

Before we dive further in, here are a few more quick facts about PostgreSQL and MySQL.

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Image created with info from PostgreSQL and Oracle

PostgreSQL vs. MySQL: Key Similarities and Differences

Similarities

The similarities between Postgres and MySQL are quite easy to spot. First and foremost, both tools store data in a relational manner. Databases contain tables, which are made up of rows and columns. Data in one table can be “related” to another tool using constructs such as primary and foreign keys. When using either Postgres or MySQL, data behaves in a very familiar way when being filtered, joined, and manipulated.

In addition to these similarities, Postgres and MySQL share several other features and functionality. Take a look at the list below!

  • Both Postgres and MySQL comply with ANSI SQL standards, meaning that most basic queries will have identical syntax.
  • Postgres and MySQL are widely adopted and integrated with several third-party tools and programming language libraries, such as Python and R.
  • Cloud providers such as AWS, Azure, and GCP provide a Platform as a Service (PaaS) offering for both Postgres and MySQL, making it easy to use these tools for any data project.

For data professionals looking to leverage Python to interact with Postgres and MySQL, check out the Using PostgreSQL in Python and MySQL in Python tutorials.

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Key Differences

While both Postgres and MySQL share many similarities, plenty of differences help to set these two offerings apart. Below, we’ll break down differences in performance and scalability, features and extensibility, and the community and usage between Postgres and MySQL.

Performance and scalability

Relational database performance is typically measured using several metrics. These might include transactions (or queries) per second, latency, throughput, and resource consumption. Different from performance, scalability is the ability of a database to handle concurrent transactions and large amounts of data.

Here, we’ll identify differences in both performance and scalability of Postgres and MySQL.

For read-heavy workflows, MySQL provides substantial performance gains over Postgres. MySQL’s default engine (InnoDB) utilizes row-level locking. This means that only the rows accessed by a transaction (or query) are “locked,” allowing for concurrent queries to operate on other rows in the same table. This results in quicker query execution when reading data from a MySQL database.

While MySQL offers a lift for read-only operations, Postgres thrives when supporting concurrent read-write operations against a database. Postgres implements multi-version concurrency control, which leverages parallel query strategies without using read or write locks.

Postgres uses robust indexing techniques and data partitioning to help improve query performance and time-to-insights as the amount of data to be stored in a database grows. This allows for Postgres to scale as the amount of data it stores grows.

Postgres generally tends to use more resources (CPU and RAM) than MySQL when running comparable workloads. Postgres’ rich set of features implements more complex query execution techniques, resulting in high resource consumption compared to MySQL. If you use either tool via a managed service provider (such as AWS or Azure), it’s easy to estimate the costs of the workload that you’ll be running.

Features and extensibility

So far, we’ve referred to both Postgres and MySQL as relational database management systems. Technically, that’s not right.

Postgres is, by definition, an object-relational database management system, or ORDBMS.

Object-relational database management systems implement much of the functionality native to traditional, relational database management systems but combine with support for object-oriented constructs. This includes inheritance, abstraction, or encapsulation.

In addition to the traditional data types that an RDBMS would support, Postgres can store and retrieve data in JSON and XML formats. This functionality enables a wider range of data to be stored, which can be quite useful in a number of applications. As an RDMS, MySQL supports more traditional data types and does not implement the same object-oriented functionality as Postgres.

Postgres is also quite extensible. One of the most notable extensions is PostGIS, which stores and retrieves geospatial data. hstore is another popular tool that’s been developed by the Postgres’ vibrant open-source community. Using a single value, hstore allows for sets of key-value pairs to be stored with Postgres. Although natively feature-rich, MySQL boasts fewer modules and plugins while ensuring core platform consistency and reliability.

Ecosystem and tooling

Both PostgreSQL and MySQL come with rich ecosystems supported by a wide range of tools, extensions, and third-party integrations, making them highly versatile for different use cases. Here’s an overview of some of the most popular tools available for each:

PostgreSQL ecosystem:

  • pgAdmin: One of the most widely used management tools for PostgreSQL, pgAdmin offers a powerful graphical interface for managing databases, running queries, and administering users. It’s highly extensible and supports all PostgreSQL features.
  • PostGIS: A robust extension that enables support for geospatial data in PostgreSQL, making it ideal for applications requiring geographic information systems (GIS). PostGIS is used in logistics, urban planning, and environmental monitoring industries.
  • TimescaleDB: Built on top of PostgreSQL, TimescaleDB enhances PostgreSQL’s capabilities for handling time-series data. It’s widely adopted in fields like IoT, finance, and monitoring systems.
  • pgBackRest: A backup and restore tool designed for PostgreSQL, offering advanced features like parallel backup and restore compression and encryption.

MySQL ecosystem:

  • MySQL Workbench: This comprehensive tool provides a unified interface for designing, developing, and managing MySQL databases. It supports database modeling, SQL development, and migration tasks.
  • Percona Server for MySQL: A free, enhanced, and fully compatible version of MySQL, offering better performance and scalability. Percona Server also includes advanced performance tuning and observability features, making it ideal for production environments.
  • Oracle Enterprise Manager: Oracle offers extensive support for MySQL through its Enterprise Manager tool, which provides monitoring, management, and security features for enterprise use cases.
  • phpMyAdmin: A popular web-based interface for managing MySQL databases, phpMyAdmin simplifies database management, especially for smaller projects or individual developers who need quick access to queries and database structure.

Cloud Integrations

All major cloud platforms, including AWS RDS, Google Cloud SQL, and Azure Database, support PostgreSQL and MySQL. These cloud services simplify database deployment and management, offering features like automated backups, scaling, and security, making them excellent choices for modern cloud-based applications.

Community

While both Postgres and MySQL are open-source tools, their communities look a little different. MySQL is heavily backed by Oracle, which provides much of the contribution, documentation, and resources for developers looking to get started with the tool. This documentation contains references and information for paid MySQL offerings provided by Oracle. Oracle also offers 24/7 support for MySQL but at a hefty price.

Postgres is supported by a prospering community of architects, developers, users, and other parties. The Postgres community is led by a core team that manages both the development and the creation and publication of documentation. This team helps to manage contributions from the wider open-source community and ensures the standardization and quality of the product that is made available.

Choosing Between PostgreSQL and MySQL

Alright! We’ve thoroughly explored the basics of Postgres and MySQL, discerned their similarities and differences, and explored their more complex features and functionality. Now, it’s time to choose the right tool to tackle your data project.

Below are several scenarios and the tool best suited to tackle each of these challenges:

Use case PostgreSQL MySQL
Large-scale enterprise applications Excellent, with robust scalability and complex query support Good, but better suited for lightweight tasks
Applications requiring geospatial data support Ideal (PostGIS support) Basic support
JSON and NoSQL-like data support Strong (supports JSON and JSONB types) Limited (basic JSON support)
High read performance (e.g., web apps) Decent, but not as optimized for reads Excellent (InnoDB engine, row-level locking)
Complex, concurrent read-write operations Superior (multi-version concurrency control) Good, but it may experience locking issues
Easy setup for small web projects Takes longer to configure Fast and easy to set up
Data warehousing and analytical processing Excellent, with powerful indexing and parallel queries Decent, but lacks advanced features

For more detail on why the respective relational database management system was selected to tackle the challenges above, make sure to keep the following in mind.

Application requirements

If you’re looking to build a robust, enterprise-grade solution, look no further than PostgreSQL. It offers a balance between a wide range of functionality and extensibility, as well as the ability to scale across an organization’s needs.

As both the amount of data and users increase, Postgres offers performance lifts over other relational databases, such as MySQL. In data architectures that leverage “data marts,” Postgres is a popular choice to support large datasets and complex queries.

When it comes to designing and developing a smaller-scale personal project, MySQL is your best bet for a fast and easy solution. From personal projects to proof-of-concepts, MySQL’s lightweight framework makes the process a breeze from start to finish. MySQL also packs a performance lift when reading data, which helps to reduce latency within data workflows.

Scalability needs

Above, we discussed a number of ways that an application or use case may scale. As you consider either Postgres or MySQL for your next project, it’s important to consider what scaling will look like.

Will data be written to a database quite frequently? How often will it be read? How many users/connections to the database will be made? Will the amount of data persisted be quite large?

Keep in mind that MySQL scales best for read-heavy workloads, while Postgres shines handling large datasets, complex queries, and a number of concurrent sessions. For smaller-scale tasks and projects, scalability may not be much of a concern and may be lower in priority when choosing between relational database providers.

Developer experience

Considering developer experience is important when choosing between tools such as Postgres and MySQL. Luckily, both database offerings provide a comfortable and mature developer experience.

The lightweight nature of MySQL helps to reduce time spent performing installation and configuration tasks, allowing developers to rapidly prototype and ship solutions. However, the feature-rich nature of Postgres may better fit the requirements of a certain application or use case, reducing the reliance on building custom solutions to implement similar functionality. As mentioned above, both offer a vibrant open-source community and strong documentation, helping to enrich an already comfortable developer experience.

Conclusion

In a space where new tools seem to spring up every week, PostgreSQL and MySQL have held their ground as two of the most popular relational database management systems available. Their wide adoption has brought about large support from their respective communities, helping to support and further develop each tool.

If you’re looking to gain more hands-on experience with Postgres and MySQL databases without having to deal with the installation or configuration, look no further than DataLab. In DataLab, you can connect to a PostgreSQL or MySQL database to work with sample data, as well as load and manipulate your own. This low-risk environment is the best place to develop and refine your SQL (and other data) skills.

As you explore both PostgreSQL and MySQL to meet the needs of your next project, make sure to check out DataCamp’s Creating PostgreSQL Databases and Functions for Manipulating Data in PostgreSQL courses. For more about MySQL, take a peek at this awesome MySQL Basics Cheat Sheet to explore the more minute features and functionality of MySQL. Happy coding!

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FAQs

Can I easily migrate from MySQL to PostgreSQL (or vice versa)?

Migrating between MySQL and PostgreSQL is possible but requires careful planning. While both databases support SQL, there are differences in syntax, data types, and functions that need to be accounted for during migration. For example:

  • Data Types: PostgreSQL supports additional data types like arrays, UUID, and JSONB, which may not have direct equivalents in MySQL.
  • Tools: There are several tools available to assist with migration, such as pgLoader (to migrate from MySQL to PostgreSQL) and MySQL Workbench (which can assist with PostgreSQL to MySQL migration). Be sure to test thoroughly, especially if you are migrating a live production database.

Is there a difference in how PostgreSQL and MySQL handle indexing?

Yes, PostgreSQL provides more sophisticated indexing options, which are essential for optimizing query performance:

  • PostgreSQL supports B-tree, hash, GIN (Generalized Inverted Index), and GiST (Generalized Search Tree) indexes. This flexibility allows PostgreSQL to optimize a wide variety of query types, from full-text searches to complex data structures.
  • MySQL primarily uses B-tree and hash indexes. While adequate for many common use cases, it lacks some of the more advanced indexing options available in PostgreSQL, which might limit optimization in complex applications.

How does the security of PostgreSQL compare to MySQL?

Both PostgreSQL and MySQL offer robust security features, including user authentication, SSL encryption, and role-based access controls. However, PostgreSQL is often considered to have more fine-grained control over access permissions and roles, making it more flexible for complex environments with multiple user types.

  • MySQL is widely used in web applications, and it integrates seamlessly with authentication systems like LDAP and PAM. However, Oracle offers enterprise-level security enhancements and support for MySQL that could be beneficial in high-security environments.

Can both PostgreSQL and MySQL handle geographic data?

PostgreSQL has a built-in extension called PostGIS that is widely regarded as the best tool for handling geospatial data. PostGIS adds support for geographic objects, allowing you to perform complex spatial queries, making it ideal for applications involving maps, geolocation, and geographical analysis.

  • MySQL also supports geographic data types (via Spatial Extensions), but its functionality is not as advanced as PostGIS in PostgreSQL. If your project involves heavy use of geographic data, PostgreSQL with PostGIS is usually the better option.

Which database is better for handling JSON and NoSQL data types?

PostgreSQL has a significant advantage when it comes to handling JSON and other semi-structured data types. It supports both JSON and JSONB (a more efficient binary JSON format), allowing developers to store and query JSON data easily, making PostgreSQL a strong choice for hybrid applications requiring both relational and NoSQL capabilities. While MySQL supports JSON data types, its functionality is more limited compared to PostgreSQL, especially in terms of indexing and querying JSON data.

How do PostgreSQL and MySQL handle ACID compliance?

Both PostgreSQL and MySQL are ACID-compliant (Atomicity, Consistency, Isolation, Durability), but they achieve this differently based on their storage engines:

  • PostgreSQL: Always ACID-compliant by default, regardless of the operation. PostgreSQL ensures transaction safety, making it highly reliable for complex operations involving large datasets.
  • MySQL: ACID compliance depends on the storage engine being used. The InnoDB engine, which is the default, is ACID-compliant, but older engines like MyISAM do not support transactions or foreign key constraints, so they are not ACID-compliant. Always check which engine is being used in MySQL to ensure compliance.

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Jake Roach
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Jake is a data engineer specializing in building resilient and scalable data infrastructure using Airflow, Databricks, and AWS. Jake is also the instructor for DataCamp's Introduction to Data Pipelines and Introduction to NoSQL course.

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