PostgreSQL vs. MySQL

PostgreSQL and MySQL are two of the most popular open-source databases available today. They both provide the database backend for many web applications, enterprise software packages, and data science projects. The two databases share some similarities in that they both adhere to the SQL standard. 

However, some key differences might influence your decision to choose one over the other. PostgreSQL is known for its advanced features, impressive durability, and scalability. MySQL is well-known for its ease of use and speed in read/write operations.

Here’s an overview of their similarities and differences, including their architectures, data types, indexing schemes, security, and performance.

PostgreSQL and MySQL similarities

Both PostgreSQL (also known as “Postgres”) and MySQL are Relational Database Management Systems (RDBMS). That means both store data in rows and tables, have a mechanism to define the relationships between the data in the tables and provide the Structured Query Language (SQL) to access the data via standardized queries.

Both database systems are ACID-compliant. ACID (atomicity, consistency, isolation, durability) compliance ensures data consistency and integrity, even in the face of system errors, hardware failures, and power outages. Both support replication for adding more servers to host data with fault tolerance and a distributed workload. 

MySQL and PostgreSQL are both free and open source, meaning that anyone can obtain the source code, install the software, and modify it how they see fit. Both offer tight integration with web servers like Apache and programming languages like PHP and Python.

Architectural differences and data types

While both MySQL and PostgreSQL are examples of an RDBMS, PostgreSQL also qualifies as an Object-Relational Database Management System or ORDBMS. This means that Postgres has the typical characteristics of a relational database, and it’s also capable of storing data as objects.

At a high level, objects in software development are models with attributes and properties that can be accessed with forms of code known as procedures and methods.

To see the difference, look at the supported data types in both systems. MySQL supports a set of standard data types, including VARCHAR (text fields limited to a certain length), TEXT (free-form text), INTEGER (an integer number), BOOLEAN (a true/false field), and DATE (a timestamp). Meanwhile, PostgreSQL supports the standard data types and a wide range of more complex data types not seen in a traditional RDBMS. This includes MONEY (a currency amount), INET (IP addresses), MACADDR (a network device’s MAC address), and many other specialized objects.

Perhaps most importantly, Postgres supports the JSON and JSONB data types, which are JSON text and binary JSON data. As most REST web service APIs today transfer data in JSON format, PostgreSQL is a favorite among app developers and system administrators. While MySQL can be made to store JSON text, the ability to natively query stored JSON data is a major advantage of PostgreSQL.

MySQL and PostgreSQL query languages

PostgreSQL supports creating custom data models with its PL/pgSQL query language, which is substantially more full-featured than MySQL’s standard SQL implementation. 

PL/pgSQL can be seen as both a query language and a procedural programming language. PL/pgSQL supports programming constructs like loops, conditional statements, variables, and error handling. The language also makes it easy to implement user-defined functions and stored procedures in queries and scripts.

MySQL’s SQL implementation lacks these features and is best suited for simple queries, data sorting, and exporting.

Even though PL/pgSQL is unique to PostgreSQL, it actually has a stricter adherence to SQL standards than MySQL’s SQL implementation. Advanced SQL features like window functions and common table expressions (CTEs) are available in PostgreSQL but not MySQL.

Database ecosystem and tools

Both PostgreSQL and MySQL boast robust ecosystems supported by various tools and integrations that enhance their functionality and streamline database management.

PostgreSQL’s ecosystem is enriched by an extensive range of open-source and commercial tools designed for automation, scaling, sharding, and migration. Tools like pgAdmin and DBeaver provide intuitive interfaces for database management, while PgBouncer and Patroni simplify connection pooling and high-availability setups. For scaling, Citus offers advanced sharding capabilities, enabling horizontal scaling for large datasets and high traffic. Migration tools like pg_upgrade ensure seamless upgrades between PostgreSQL versions, while Ora2Pg facilitates migration from Oracle databases.

MySQL’s ecosystem is equally expansive, with tools catering to various database management needs. MySQL Workbench provides a comprehensive graphical interface for database design, administration, and performance tuning. For scaling, MySQL supports sharding through ProxySQL and Vitess, which allow for horizontal scaling and improved database performance. Percona Toolkit and AWS Database Migration Service (DMS) streamline migrations, making it easier for enterprises to transition to or from MySQL.

Both ecosystems support automation tools like Ansible and Terraform for infrastructure management, ensuring smoother deployment and scaling of database instances. Whether you choose PostgreSQL or MySQL, the ecosystems offer many tools to optimize database performance and simplify complex operations.

Indexing Methods

Indexes are crucial for database performance, speeding up data retrieval and optimizing queries. PostgreSQL and MySQL offer various indexing methods to suit different use cases:

• B-Tree Indexing: The default method in both databases, ideal for efficient data retrieval in large datasets.
• GiN & GiST Indexing: PostgreSQL-specific, designed for complex data types like arrays, JSON, and full-text search.
• R-Tree Indexing: Suitable for spatial data (points, lines, polygons), enabling faster geospatial queries.
• Hash Indexing: MySQL-specific, uses hash tables for efficient equality-based lookups but not range queries.
• Full-Text Indexing: Supports advanced text searches with keywords and phrases in both databases.

Choosing the right index type boosts query performance and ensures your database meets application demands.

PostgreSQL vs MySQL performance and scalability 

Both PostgreSQL and MySQL are capable of scaling to handle large amounts of data and high levels of traffic and to support complex applications. However, scaling MySQL typically involves adding more hardware and database instances, while PostgreSQL has some advanced features that naturally support scaling.

PostgreSQL uses a system called MVCC (Multiversion Concurrency Control) that allows multiple users to access and modify data simultaneously without locking out or slowing down each other’s queries like MySQL. This is particularly helpful for applications requiring high read/write activity levels.

When adding additional servers, MySQL uses binary log-based replications, which is fast but can lead to data inconsistencies when network hiccups interrupt replication activities. PostgreSQL uses the “log-shipping” approach, which is more reliable but can be slower than binary log replication. However, PostgreSQL also supports table partitioning, which allows a single table to be spread across multiple smaller tables. This tends to improve performance because smaller amounts of data are queried simultaneously.

PostgreSQL also has a more advanced query optimizer than MySQL, which helps execute queries more efficiently. PostgreSQL also sports a larger maximum table size than MySQL, making it better suited for applications with large datasets.

Security

PostgreSQL and MySQL take different approaches to security. Both have mechanisms for granting access to schemas and tables to defined users, but PostgreSQL offers more advanced features.

PostgreSQL has a fine-grained approach to user privileges, allowing administrators to assign more specific user privileges and roles. MySQL, however, uses a broader and more basic authorization system with a combination of user accounts and global or database-specific privileges. PostgreSQL supports many authentication methods beyond the simple username and password combination. This includes authenticating against an LDAP server or Active Directory and certificate-based authentication.

Both systems support encryption, with PostgreSQL offering more options. In particular, PostgreSQL supports column-level encryption and a feature known as Transparent Data Encryption (TDE). With TDE, all data in a schema is encrypted using a symmetric encryption key. This key, in turn, is protected by a master key that can be stored in a software key management system or a hardware-based security module.

MySQL uses SSL (Secure Sockets Layer) to help ensure data integrity, which makes it a popular database for web applications. Beyond that, MySQL doesn’t offer as many security and encryption features as PostgreSQL. But that doesn’t mean it’s insecure. A MySQL installation can be secured well enough to meet enterprise standards through the judicious use of strong passwords and network-level security.

Transactions

An RDBMS’s transaction methodology ensures data consistency and integrity while playing a large part in the database’s overall performance. The speed at which transactions are performed defines whether a database system suits a particular task.

Since both PostgreSQL and MySQL are ACID-compliant, both support transaction rollbacks and commits. However, MySQL does not enable transactions by default, opting for “auto-commit” mode out of the box. This means each SQL statement is automatically committed or rolled back unless this setting is changed.

MySQL uses a locking mechanism optimized for performance but can lead to inconsistencies in some cases. PostgreSQL uses a strict locking mechanism for a higher level of consistency.

Community support

MySQL first gained popularity in Web 1.0 days, partly because it’s open source and works well with other free and open-source software such as the PHP language and operating systems built on the Linux kernel. A strong community has built around MySQL over time, making it one of the most popular open-source packages ever. 

The well-known acronym LAMP—for Linux, Apache, MySQL, and PHP (or Perl, or Python)—came from this community in honor of the free software packages that have powered many dynamic websites for decades.

MySQL was created by Swedish developers Michael Widenius and David Axmark in 1995. A year later, the two founded the company MySQL AB to provide commercial support and consulting services for the database as it grew in popularity. In 2008, Sun Microsystems acquired MySQL AB for $1 billion. Two years later, Sun was acquired by Oracle Corporation, which means the tech giant owns MySQL.

This raised concerns in the open-source community that Oracle would prioritize its own proprietary RDBMS solutions over MySQL. These fears have mostly been unfounded, as Oracle continues to develop MySQL and offer it under the GNU General Public License (GPL), making it free for personal and non-commercial use. However, the GPL allows Oracle to charge for commercial uses of MySQL, which makes some in the community no longer consider MySQL to truly be “free and open source.”

In response to these concerns, a community-supported version of MySQL has emerged called MariaDB. While identical to MySQL in basic form and function, MariaDB lacks some of MySQL’s advanced features.

PostgreSQL is released under a modified version of the MIT license known as the PostgreSQL License. This is a permissive free and open-source license, allowing users a great deal of flexibility in how they can use and modify the software. 

As a result, PostgreSQL remains one of the most popular open-source databases in the world, with a large community support base of many users, enterprise admins, and application developers. However, there are more community contributions to the MySQL and MariaDB ecosystems.

Recent developments

Both PostgreSQL and MySQL have introduced notable updates in recent versions, keeping them at the forefront of open-source database innovation.

The release of PostgreSQL 17 in September 2024 brought several advancements. A new memory management system for the VACUUM process reduces memory consumption and improves overall performance. SQL/JSON capabilities were expanded with functions like JSON_TABLE(), enabling seamless transformation of JSON data into table formats. Logical replication has seen enhancements, such as failover control and incremental backup support via pg_basebackup. Query performance improvements include optimized handling of sequential reads and high-concurrency write operations. PostgreSQL 17 also introduced a COPY command option, ON_ERROR ignore, which enhances data ingestion workflows by continuing operations even when encountering errors.

MySQL 8.0.40, released in October 2024, continues to refine database performance and compliance. Enhancements to the InnoDB storage engine improve adaptive hash indexing and parallel query performance. Security has been bolstered with updates to OpenSSL 3.0.15 integration, ensuring compliance with modern encryption standards. The introduction of the –system-command option allows for finer control over client commands, and a revamped sys schema improves the performance of key views like innodb_lock_waits. MySQL also focuses on developer flexibility with improved error handling and broader compatibility for tools and libraries.

These ongoing developments highlight the commitment of both database communities to addressing evolving performance, scalability, and security needs, ensuring their continued relevance in diverse application environments.

Use cases

MySQL is utilized by an untold number of websites thanks in part to the database being free and open source, as well as its out-of-the-box support for the PHP language. The combination of PHP and MySQL helped create a rush of dynamic websites that didn’t have their HTML code manually updated.

Early on, Google used MySQL for its search engine. Over time, as the search giant’s dataset grew, it moved to different database technologies optimized for unstructured data and fuzzy searches. (Today, Google search is powered by Google’s own distributed data storage system, Bigtable.)

MySQL is still widely used for many small- to medium-sized web applications. Content management systems and specialized web apps like Geographic Information Systems (GIS) almost always support MySQL as a database backend.

Many enterprises also use it as the data backend for their internal applications and data warehouses. PostgreSQL is used in many of the same scenarios. Most web apps that support MySQL will also support PostgreSQL, making the choice a matter of preference for sysadmins and database administrators.

PostgreSQL pros and cons

Here are some of the pros of choosing PostgreSQL:

• Performance and scalability that matches commercial RDBMS products.
• Concurrency support for multiple write operations and reads at the same time.
• The PL/pgSQL language and support for other programming languages, such as Java, JavaScript, C++, Python, and Ruby.
• Support for high availability of services and a reputation for durability.

Some of the cons of PostgreSQL include:

• It can be complex to set up and manage, particularly for newcomers.
• Reliability comes at a performance cost.
• Large databases used in complex applications can be memory intensive.
• Less community support than MySQL/MariaDB.

MySQL pros and cons

The pros of MySQL include:

• MySQL’s storage engines enable fast performance.
• A  small footprint and an easy-to-use replication system make it easy to grow and scale.
• Open-source solid community support.
• Nearly all web applications and enterprise systems support MySQL.

Here are some cons of choosing MySQL:

• Not as scalable as PostgreSQL or newer database systems.
• Lack of advanced features like full-text search and complex data types.
• Less resilience when processing complex queries.
• There is no built-in support for backups, requiring third-party backup software.

PostgreSQL and MySQL: Which to choose?

Both PostgreSQL and MySQL are extremely capable RDBMS packages. While PostgreSQL clearly supports more advanced features and has a greater reputation for reliability, that doesn’t mean MySQL is a bad choice.

MySQL’s relative simplicity makes it a great choice for smaller and medium-sized web applications. Those new to SQL and RDBMS applications, in general, can pick up the basics of MySQL quickly, making it a great choice for enterprises with limited IT resources. MySQL also has a strong community, with decades of apps supporting MySQL.

If you will be dealing with a larger dataset or developing complex custom applications, PostgreSQL is an excellent choice. Its support for custom data types and the PL/pgSQL language make Postgres a favorite of sysadmins, web developers, and database administrators worldwide.

PostgreSQL vs MySQL: A side-by-side comparison

Choose the right database, monitor with ease

Selecting between a PostgreSQL and MySQL database ultimately depends on your specific project requirements. PostgreSQL excels in handling complex queries, large datasets, and enterprise-grade features, making it ideal for analytics, REST APIs, and custom applications. MySQL, on the other hand, shines in simplicity, speed, and compatibility, making it perfect for small-to-medium-sized applications and high-traffic web platforms.

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