PostgreSQL vs MySQL: A Detailed Comparison for Data Engineers
MySQL and PostgreSQL are the top two open-source relational databases. They are used in countless commercial, enterprise, and open-source applications.
PostgreSQL and MySQL have been around for decades. They’re both reputed data management systems with features to enable replication, clustering, fault tolerance, and integration with many third-party tools.
But, the two databases have several significant differences, and understanding these distinctions is the key to picking the right solution for your project.
In this article, we will give an overview of PostgreSQL and MySQL before diving into the seven key differences between Postgres vs. MySQL.
PostgreSQL, or Postgres, is an open-source object-relational database management system (RDBMS).
The first production release of Postgres was in 1997, and it has since evolved into a highly advanced, robust database management system with features like transactions, triggers, views, and stored procedures.
PostgreSQL is an object-relational database. It combines the principles of a traditional relational database with the data model used in object oriented databases. This makes it highly scalable and suitable for diverse environments, from small-scale applications to large-scale enterprise deployments.
The database can support simple transaction processing in OLTP workloads, complex analytical queries, and frequent write operations during OLAP processes.
Key features and strengths
- Extensibility: PostgreSQL enables users to add custom functionality to the database using various extension mechanisms, including User-defined Functions (UDFs), custom data types, procedural languages, and Foreign Data Wrappers (FDWs).
- Conformance to SQL standards: PostgreSQL has been actively developing and adhering to the Structured Query Language (SQL) standards. It supports standard SQL syntax, functions, and data types. SQL transactions are also fully ACID compliant.
- Advanced data types: The software supports unique data types, like arrays, JSON, range, Boolean, geometric, Hstore, and network address types.
- Robust indexing: PostgreSQL provides dynamic indexing options, including B-Tree indexes, hash indexes, GiST indexes, GIN indexes, and BRIN indexes. It also supports partial indexes.
MySQL is the leading relational database used by developers. It is a purely relational database management system (RDBMS) released in 1995. It uses structured query language (SQL) to access and manage data.
Businesses of all sizes use MySQL for efficient data management. It powers well-known web applications, like WordPress and Joomla, and is used in mission-critical operations at leading global companies, including Facebook, Netflix, and Google.
MySQL is known for its speed and reliability, especially for highly concurrent, read-only functions. It can be used for OLTP transaction processing and applications operating on the LAMP (Linux, Apache, MySQL, and PHP/Python/Perl) open-source software stack.
A MySQL database can be scaled horizontally and has extensive cross-platform compatibility. It also provides built-in replication and clustering capabilities to improve availability and fault tolerance.
MySQL has effective data security features and supports multiple storage engines, including InnoDB and MyISAM, which provide different trade-offs between performance and data integrity.
Key features and strengths
- Speed and performance: MySQL has a built-in query optimizer for rapid query performance. Developers can also use indexing, caching, and varying storage engines to handle large datasets with low latency and high throughput.
- Wide adoption and large community: Given MySQL’s widespread prevalence, the platform has a large and active online community of developers and enthusiasts that provide support, contribute code, and share knowledge.
- Replication and high availability: MySQL enables seamless and quick database replication using topologies, custom replication filters, and two replication modes - Asynchronous and Semi-asynchronous.
- Ease of use: The database has consistently ranked as one of the easiest tools to install and configure. It also has a user-friendly interface for database management and a command-line interface for more advanced users.
PostgreSQL vs MySQL Comparison
Here’s a table comparing the characteristics and features of each relational database management system:
The speed and performance of PostgreSQL and MySQL databases depend on software and hardware configurations. However, each database serves different use cases.
PostgreSQL is designed for complex operations on large datasets that contain different data types. Performance is measured by its ability to quickly execute advanced queries, Disk I/O, concurrency controls, and query profiling.
MySQL databases are built to process simple transactions in near real-time. Performance is measured by query response times and concurrency controls to maintain data integrity.
Both database systems also offer features to tune performance. These are primarily related to query optimization and indexing.
PostgreSQL and MySQL have common query optimization capabilities, including indexing, connection pooling, and table partitioning. However, there are individual optimization techniques for each platform.
In PostgreSQL, developers can boost performance using a sophisticated query planner, materialized views, full-text search, and parallel query execution.
In MySQL, developers can use the EXPLAIN command to view the query execution plan and enhance query response times using stored procedures and caching mechanisms, including InnoDB buffer pool, MyISAM key cache, and a built-in query cache that stores the results of SELECT statements.
Indexing is an important data structure technique that makes it easier to locate and retrieve data without searching the entire database.
MySQL and PostgreSQL support many indexing options to speed up queries of large data sets.
In MySQL, data engineers can use B-tree, spatial, R-tree, full-text, and hash indexes.
PostgreSQL supports the above indexes and has additional options for different data types, including GIN (Generalized Inverted Index), SP-GiST (Space-Partitioned Generalized Search Tree), GiST (Generalized Search Tree), and BRIN (Block Range Index). PostgreSQL also supports partial and expression indexes.
ACID Compliance and Concurrency Control
Compliance with the ACID (Atomicity, Consistency, Isolation, and Durability) properties of transactions guarantees that database transactions are processed reliably and accurately.
ACID compliance is also important for concurrency control, which ensures that multiple transactions can read and write to the same data without interfering with each other or producing incorrect results.
Postgres is ACID compliant, while MySQL’s default storage engine, InnoDB, is also ACID compliant. However, the level of compliance might change depending on which storage engine you choose in MySQL.
To maintain transactional integrity and implement concurrency control, both database management systems offer features like:
- Transaction isolation levels: PostgreSQL and MySQL support different levels of transaction isolation, such as Read Committed, Repeatable Read, and Serializable. These levels provide different trade-offs between concurrency and consistency.
- Locking mechanisms: Locking mechanisms prevent conflicts between concurrent transactions that access or modify the same data. PostgreSQL and MySQL support pessimistic and optimistic locking mechanisms. They also provide different locking levels, such as row-level, page-level, or table-level locking. PostgreSQL also supports advisory locks.
- Multi-version concurrency control (MVCC): MVCC involves maintaining multiple versions of data. It enables multiple transactions to access the same data simultaneously by providing each transaction with a snapshot at the time of the transaction’s start.
MVCC can improve performance and scalability compared to lock-based concurrency control but can also lead to increased storage requirements and complexity.
PostgreSQL uses a multi-version concurrency control (MVCC) approach by default, while MySQL uses a combination of lock-based and MVCC concurrency control depending on the storage engine.
Extensibility is the ability of a database system to be extended with custom functionality. It allows developers to tailor the system to their specific needs and requirements.
PostgreSQL’s extensibility features
PostgreSQL is rated for its extensibility. Key customization features include:
- User-defined functions (UDFs): PostgreSQL allows developers to create UDFs in several programming languages. UDFs can be used to implement custom logic, such as data transformations, and can be called from SQL queries or other functions.
- Procedural languages: PostgreSQL supports several procedural languages, including PL/pgSQL, PL/Python, and PL/SQL, to write stored procedures, triggers, and other server-side code directly in the database.
- Custom data types: Developers can define custom data formats to represent complex or domain-specific data structures using the PostgreSQL API.
- Extensions: PostgreSQL allows third-party database developers to create and distribute add-ons that extend the functionality. The PostgreSQL community provides many extensions, including PostGIS (for geographic data distribution), pgAdmin (for database administration), and many more.
- Foreign data wrappers (FDWs): PostgreSQL’s FDW feature allows developers to access data from external sources (such as other databases, web services, or file systems) as if it were a table in the database. FDWs can integrate external data into PostgreSQL-based applications.
MySQL’s extensibility features
MySQL also supports UDFs and enables stored procedures and triggers in several programming languages. It also offers.
- Pluggable Storage Engines: Developers can use different data storage technologies to store data in MySQL.
- MySQL Connectors: MySQL provides connectors for several programming languages, including C, C++, Java, .NET, Perl, Python, and Ruby. These connectors allow developers to connect to MySQL from their applications and use MySQL as a data storage and retrieval engine.
- MySQL Enterprise Edition: MySQL Enterprise Edition is a commercial version of MySQL that includes several proprietary extensions and plugins, including MySQL Enterprise Monitor (for monitoring and management), MySQL Enterprise Backup (for backup and recovery), and MySQL Enterprise Security (for advanced security features).
Overall, PostgreSQL provides more customization and extension options. This gives developers the flexibility and power to create custom functionalities that can be tightly integrated with the database system.
PostgreSQL and MySQL allow users to store and manage data sets containing different data types. Here are the data types that both platforms support:
- Numeric: integer, decimal, float, etc.
- Character: varchar, text, char, etc.
- Date/Time: date, time, timestamp, year, etc.
- Binary: blob, binary, etc.
- JSON and spatial data types (starting from MySQL 5.7)
In addition to these, PostgreSQL allows users to work with advanced data types:
- Arrays: PostgreSQL allows you to define arrays of any built-in or user-defined data type.
- Hstore: Hstore allows you to store arbitrary key-value pairs within a single PostgreSQL column.
- JSON: PostgreSQL has built-in support for storing and querying JSON data.
- Range types: PostgreSQL allows you to define range types representing a range of values.
- Geospatial data types and functions: PostgreSQL works with geospatial data types, including point, line, polygon, and geography. It also functions for working with geospatial data, including ST_Contains, ST_Distance, ST_Intersects, and more.
PostgreSQL’s advanced data types make it a powerful tool for building dynamic data-driven applications.
Data functions are used to manipulate, analyze, and transform data in a database management system. Here are some data functions available in both PostgreSQL and MySQL:
- Mathematical functions: abs, sqrt, pow, etc.
- String functions: concat, substring, replace, etc.
- Date/time functions: date_add, date_sub, datediff, etc.
- Aggregate functions: count, sum, avg, max, min, etc.
- Control flow functions: if, case, etc.
- Full-text search functions: match, against, etc.
PostgreSQL provides additional data functions, including:
- Window functions: rank, dense_rank, row_number, etc.
- Geospatial functions: ST_Distance, ST_Contains, ST_Intersects, etc.
- Full-text search functions: to_tsvector, to_tsquery, etc.
Developers can also create custom data types and functions on PostgreSQL, making the database system highly flexible.
Licensing and Costs
PostgreSQL is open-source and released under the PostgreSQL License. It is free to use, modify, and distribute the software for commercial and non-commercial purposes without licensing fees.
MySQL is available under two licensing options: the open-source GNU General Public License (GPL) and a commercial license under Oracle Corporation. The open-source version is free to use, modify, and distribute, but any derivative work must also be licensed under the GPL.
The commercial license is for organizations that do not want to distribute their software under the GPL and want to leverage Oracle’s customer support. The cost of the commercial license varies depending on the type of support and services you require.
Community and Ecosystem
PostgreSQL’s community support and ecosystem
PostgreSQL has a large community of users who contribute to its development and support.
The PostgreSQL Global Development Group (PGDG) oversees the development and release of PostgreSQL, and the community contributes to its development through code contributions, bug reporting, and testing.
PostgreSQL has an extensive ecosystem of third-party tools, libraries, and frameworks that extend its functionality. The community also provides a range of resources for support and documentation, including official documentation, mailing lists, forums, and IRC channels.
MySQL’s community support and ecosystem
MySQL is supported by a diverse community of developers and users and a vast ecosystem of third-party tools and applications.
Many third-party developers contribute plugins, extensions, and patches to enhance MySQL’s functionality and performance. In addition, MySQL’s documentation is comprehensive and user-friendly.
MySQL also has an active online community known for its helpful and supportive nature. Users can often get assistance and advice to troubleshoot MySQL issues from experienced developers. This extensive ecosystem contributes to MySQL’s popularity across industries.
Use Cases and Examples
Deciding which database to use for your project can be challenging. Here are a few use cases for PostgreSQL and MySQL:
When to choose PostgreSQL
Complex applications requiring custom functions or operators
PostgreSQL is commonly used in applications to run complicated queries that require advanced database features and high scalability. Examples include:
- Financial applications that require robust transaction management and compliance with regulatory requirements.
- E-commerce applications that require advanced data modeling and complex queries.
- Data analytics and business intelligence tools that need advanced data processing and analysis capabilities.
Projects that demand strict adherence to SQL standards
PostgreSQL is a popular choice for projects that demand strict adherence to SQL standards. Examples include:
- Government agency projects that require interoperability between different systems.
- Enterprise applications
- Academic and research projects that require reproducibility and consistency of data.
Applications that benefit from advanced data types
PostgreSQL can be beneficial in applications that involve complex data structures and relationships. Examples include:
- Geographic Information Systems (GIS) applications that often use complex data structures such as points, lines, and polygons.
- Content Management Systems (CMS) applications that have hierarchical data structures such as trees and graphs.
- Financial applications that use arrays, ranges, and intervals.
- IoT and sensor data applications often involve time-series data. This can be represented using advanced data types like timestamps, intervals, and arrays.
When to choose MySQL
Web applications prioritizing performance and ease of use
MySQL is easy to configure and use. It can also handle large volumes of data and transactions, making it well-suited for high-traffic web applications. Examples include:
- E-commerce applications use MySQL to store product catalogs, customer data, and transaction records.
- Content management systems (CMS) such as WordPress and Drupal to store and manage website content.
- MySQL is often used in embedded applications, such as point-of-sale systems and digital signage, to store and manage data locally on the device.
Applications that require high availability through replication
MySQL enables quick database replication and is used in applications where high availability and fault tolerance are critical. Examples include:
- Financial services companies that require high availability to ensure that transactions are processed quickly and accurately.
- Healthcare providers that need access to patient data at all times.
- Online gaming platforms that must ensure that players can access and play games without any downtime.
- Social media platforms that must always be available for users to access and post updates.
Projects with smaller budgets or limited resources
MySQL is a good option for small to medium-sized projects with limited budgets or resources. Examples include:
- Small businesses can use MySQL to power their websites and web applications.
- Educational institutions can use MySQL to manage student information, course catalogs, and other academic data.
- MySQL can store data from IoT sensors and other embedded devices with limited processing power and memory.
- MySQL is easy to learn and use. It could also be more affordable for small-scale mobile and web application developers.
Data teams often have evolving needs and might need to migrate from MySQL to PostgreSQL or vice versa.
Migrating from MySQL to PostgreSQL
Data teams choose to move from MySQL to PostgreSQL because:
- They need more advanced features for complex queries
- They need stronger compliance with SQL standards
- They want to model complex data
- PostgreSQL is entirely free to use
- They require support for specific project requirements
Challenges and common issues
Migrating from MySQL to PostgreSQL is a complex process, and several challenges may arise. These include:
- Syntax differences
- Data type conversions
- Different approaches to database performance
- Indexing ad stored procedure differences
- Migration tool limitations
- Application dependencies
Tools and strategies for migration
Here are some standard tools and strategies for migrating from MySQL to PostgreSQL:
- Manual migration: This involves manually exporting data from MySQL and importing it into PostgreSQL. This can be time-consuming and error-prone, but you get total control over the migration process.
- Third-party migration tools: Several third-party tools are available that can automate migration between database systems. Examples include the Airbyte, AWS Database Migration Service, and the AWS Schema Conversion Tool.
- Application-level migration: Rather than migrating the entire database simultaneously, you can gradually migrate individual applications or components. This can reduce the complexity of the migration and allow you to identify and resolve issues more easily.
- Testing and validation: Regardless of your chosen migration strategy, it’s essential to thoroughly test and validate the new PostgreSQL database before switching over completely. This can help identify any issues before they cause problems in production.
Migrating from PostgreSQL to MySQL
While it’s less common than migrating from MySQL to PostgreSQL, there may be cases where organizations or individuals choose to migrate from PostgreSQL to MySQL. Some reasons for this might include:
- MySQL has been around for longer, which may make it a more familiar choice for developers or organizations that have used it before.
- MySQL has a larger ecosystem of third-party tools and applications.
- MySQL is better suited for their specific workloads or use cases.
Challenges and common issues
Migrating from PostgreSQL to MySQL may involve the following challenges and common issues:
- Data type incompatibility since PostgreSQL supports more advanced data types.
- Syntax and performance differences
- Fewer functionalities in MySQL compared to PostgreSQL
- Data loss during migration
- Migration tools that are not compatible with all versions of the databases
Tools and strategies for migration
Some tools and strategies that can help simplify the migration process include:
- Database migration tools: Several database migration tools automate the process, including Airbyte and Full Convert. They can help convert schema, data, and functions from PostgreSQL to MySQL.
- Analyze the PostgreSQL database: Before starting the migration process, it is important to analyze the PostgreSQL database to identify any potential issues.
- Plan the migration process: Carefully plan the migration process, including the migration order, data mapping, and testing, to minimize the risk of data loss or corruption.
- Convert data types and functions: PostgreSQL and MySQL use different data types and functions. Converting them before migrating the data may be necessary. This can be done manually or through automated tools.
- Test the migrated data: Thoroughly test the migrated data to ensure data consistency and accuracy.
- Optimize the MySQL database: After migration, optimize the MySQL sorry database to ensure optimal performance and scalability.
PostgreSQL and MySQL are two highly efficient relational database management systems. They differ in the data types and functions they support, their level of ACID compliance, and the indexing options they provide.
Postgres is a feature-rich database used for complex analytical workloads, whereas MySQL is a simple web database that powers websites.
Every new release bridges the gap between the two databases. Still, data engineers must analyze the specific needs and requirements of the project to make an informed decision about which solution to use.
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