October 20, 2024
Summary: MySQL and PostgreSQL offer many of the same features and capabilities, but there are many differences between these two open-source databases.
Table of Contents
Introduction
Both PostgreSQL and MySQL are widely used open source databases that power a variety of real-time applications. While MySQL is recognized as the world’s most popular database, PostgreSQL is often described as the world’s most advanced relational database management system (RDBMS). Unlike PostgreSQL, MySQL does not fully comply with SQL standards and lacks many of the features available in PostgreSQL, which is why PostgreSQL is growing increasingly popular and becoming the preferred choice among developers.
Following Oracle’s acquisition of MySQL, the database now has two versions: enterprise and open source, with the latter facing criticism from users due to Oracle’s control over MySQL’s development. Conversely, PostgreSQL is favored globally due to its comprehensive list of enterprise-grade features and capabilities. It is developed by a global community committed to enhancing PostgreSQL’s offerings through significant contributions from various companies, ensuring that it remains feature-rich and highly competitive with other open source and commercial databases.
Why PostgreSQL?
PostgreSQL is an open source, feature-rich object-relational database management system (ORDBMS) that competes with real-time, top-ranked databases such as Oracle. Developers also choose PostgreSQL as their NoSQL database since it simplifies the setup and use of databases both on-premises and in the cloud. In environments with numerous databases on a private or public cloud, automating the building of PostgreSQL instances can save a significant amount of time. It is also widely adopted across all platforms, including Docker containers.
What Kind of Applications?
PostgreSQL, being fully ACID-compliant and enterprise-grade, is both developer and DBA-friendly. It is the best choice for high-transactional and complex applications across any domain and can cater to various web and mobile-based application services. Additionally, PostgreSQL serves as an excellent data warehouse for running complex reporting queries and procedures on large volumes of data.
Why MySQL?
MySQL is available in both open source and commercial versions, with the commercial version managed by Oracle. As an RDBMS database, it is simple to set up and use but may not be ideal for applications requiring full SQL compliance. MySQL has significant limitations regarding SQL standards, making it more suitable for simple web applications that handle smaller volumes of data on a fault-tolerant database. Additionally, the integration capabilities of MySQL are constrained, which complicates its use in heterogeneous database environments.
What Kind of Applications?
MySQL is a partially SQL-compliant database suitable for simple web applications or applications that require a straightforward schema design and simple SQL query operations. It is not an ideal choice for complex applications that deal with large volumes of data.
Data Types
PostgreSQL vs. MySQL Data Types Comparison Table
Data Type | PostgreSQL | MySQL |
---|---|---|
32 bit integer | INT | INT |
16 bit integer | SMALLINT | SMALLINT |
64 bit integer | BIGINT | BIGINT |
Automatically incremented 32 bit integer | SERIAL | INT, with AUTO_INCREMENT |
Automatically incremented 16 bit integer | SMALLSERIAL | SMALLINT, with AUTO_INCREMENT |
Automatically incremented 64 bit integer | BIGSERIAL | BIGINT, with AUTO_INCREMENT |
Bit value | BIT | BIT |
1, 0 or NULL | BOOLEAN | TINYINT(1) |
Floating point number | REAL | FLOAT |
Double precision floating point number | DOUBLE PRECISION | DOUBLE |
Fixed point number | NUMERIC | DECIMAL |
Currency amount (32 bit) | MONEY | DECIMAL(19,2) |
Fixed length char string, 1 <= n <=8000 | CHAR | CHAR/LONGTEXT |
Variable length char string, 1 <= n <=8000 | VARCHAR | VARCHAR/MEDIUMTEXT/LONGTEXT |
Date (no time of day) | DATE | DATE |
Time of day (no date) | TIME | TIME |
Both date and time | TIMESTAMP | DATETIME |
Time interval | INTERVAL | TIME |
Variable length byte string, <= 2GB | BYTEA | LONGBLOB |
Variable length char string, <= 2GB | TEXT | LONGTEXT |
UUID (36 byte) | UUID | VARCHAR(36) |
XML formatted string | XML | LONGTEXT |
JSON formatted string | JSON | LONGTEXT |
Text search vector | TSVECTOR | LONGTEXT |
Text search query | TSQUERY | LONGTEXT |
Geometric type | POINT | POINT |
Geometric type | LINE | LINESTRING |
Geometric type | LSEG | LINESTRING |
Geometric type | BOX | POLYGON |
Geometric type | PATH | LINESTRING |
Geometric type | POLYGON | POLYGON |
Geometric type | CIRCLE | POLYGON |
Use Cases
PostgreSQL
PostgreSQL is pretty much everywhere — it stands within the top four most used databases today, just behind MySQL. Major companies like Bloomberg, Goldman Sachs, and Nokia have PostgreSQL running at their backend.
PostgreSQL can be used by various industries and isn’t limited to just one sector. Here are a couple of examples in which PostgreSQL is widely used today.
- Government GIS data: PostgreSQL contains a powerful extension called “PostGIS.” This extension provides many functions that assist in processing different geometric forms like points, line strings and is optimized to reduce disk and memory footprint, thus improving query performance. Electricity, emergency services, and water infrastructure services are primarily dependent on GIS to locate crew members and direct them to accurate destinations, often under challenging conditions, thus, coming in handy for the government.
- Manufacturing: Many manufacturing industries demand a lot of data storage facilities at high levels of efficiency. PostgreSQL is a suitable choice for optimizing supply chain performance and storage. It is the preferred choice since it is ACID-compliant and can be configured for automatic failover, full redundancy, and almost-zero-downtime upgrades. Since Oracle’s new licensing policy has made it difficult for smaller businesses to sustain the cost of using Oracle, PostgreSQL is preferred.
- Web technology: PostgreSQL is not just a relational database; it can also serve as a NoSQL-style data store. You can have both — the relational and the document-oriented world — in a single product. It can function in many modern frameworks like Django (Python), Hibernate (Java), Ruby on Rails, PHP, etc. Due to its replication ability, websites can easily be scaled out to incorporate as many database servers as you need.
- Scientific data: Research and scientific projects can generate terabytes of data, which must be handled in the most practical way possible. PostgreSQL has excellent analytical capabilities and offers a powerful SQL engine, so processing large amounts of data won’t cause issues. PostgreSQL can also be extended easily. You can integrate Matlab and R to perform several mathematical and aggregation functions.
MySQL
MySQL proves to be useful for web applications as most servers rely on MySQL. Other than being used as a WordPress database, many non-WordPress businesses like Joomla, TYPO3, and Drupal also use MySQL as their primary database.
Here are a few use cases of MySQL that prove it to be a reliable and efficient database system:
- OLTP transactions: Transactions require speed and accuracy. MYSQL can be scaled to 1000s of queries per second with efficiency and ease. The transaction needs to ensure Atomicity, Consistency, Isolation, and Durability (ACID). MySQL also adheres to the ACID principles, making it safe for critical transactions. If a system fails during a transaction, it rolls back the failed transactions.
- LAMP open-source stack: MySQL is essential to numerous applications operating on the LAMP open-source software stack (LAMP stands for Linux, Apache, MySQL, and PHP/Python/Perl). LAMP is a universal solution stack for web services and is widely regarded as the medium of choice for both dynamic websites and high-performance web applications.
- E-commerce applications: MySQL is one of the most prevalent transactional machines for eCommerce platforms. It’s beneficial for managing customer data, transactions, and product catalogs. In ecommerce solutions, MySQL is often used simultaneously with other, non-relational databases, including document and key-value stores for syncing order data, and storing non-product data.
JSON Support
PostgreSQL
PostgreSQL began supporting JSON data types with Version 9.2, offering more advanced JSON data capabilities than MySQL. It includes a wide range of JSON-specific operators and functions that facilitate efficient data searches within JSON documents. The JSONB feature from PostgreSQL Version 9.4, which stores JSON in a binary format, also supports Full-Text Indexing — otherwise known as GIN Indexing. This enhancement significantly speeds up Full-Text searches on JSON documents.
MySQL
In contrast, MySQL introduced support for JSON data types much later, starting with Version 5.7. While JSON data columns can be queried using SQL and JSON attributes can be indexed, the range of JSON-specific functions is limited compared to PostgreSQL. A significant constraint of MySQL is its lack of support for Full-Text Indexing on JSON columns. Since MySQL is not fully SQL-compliant, it may not be the best choice for storing and processing JSON data.
Indexes
To improve database performance, you can speed up SQL queries by using indexes when tackling large data tables. Without indexes, queries would be slow and a major burden for the DBMS.
Both PostgreSQL and MySQL offer distinct indexing options. PostgreSQL index types include the following:
- Partial indexes that only arrange information from a section of the table
- B-tree indexes and hash indexes
- Expression indexes that generate an index resulting from express functions instead of column values
MySQL, on the other hand, offers the following index options:
- Indexes stored on R-trees, such as indexes found on spatial data types
- Indexes stored on B-trees, such as PRIMARY KEY, INDEX, FULLTEXT, and UNIQUE
- Inverted lists and hash indexes when utilizing FULLTEXT indexes
Architecture
MySQL is a purely relational database, whereas PostgreSQL is an object-relational database. PostgreSQL offers more sophisticated data types, and lets objects inherit properties. On the flip side, it also makes it more complex to work with PostgreSQL. PostgreSQL houses a single, ACID-compliant storage engine. MySQL offers support for 15 different storage engines apart from its default storage engine, InnoDB. The vast array of storage engines allows you to quickly leverage them for other use cases.
PostgreSQL generates a new system process via memory allocation for every client connection established. This requires a lot of memory on systems with many client connections, but it provides better isolation, e.g. an invalid memory access bug only crashes a single process instead of the entire database server. On the other hand, MySQL utilizes a single process and maintains a single thread for every connection. This makes MySQL the more suitable choice for applications of less-than-enterprise scope.
Replication and Clustering
Both MySQL and PostgreSQL offer replication and clustering capabilities, allowing data operations to be distributed horizontally.
PostgreSQL
PostgreSQL replication is well-regarded for its reliability. Unlike MySQL, PostgreSQL’s replication is based on WAL files, making it faster, more dependable, and easier to manage. PostgreSQL supports the configuration of primary-replica and primary-to-multiple-replicas, including cascading replication. Termed as streaming or physical replication, it can be either synchronous or asynchronous.
By default, replication is asynchronous, with replicas catering to read requests. For applications that require data snapshots on replicas to mirror the primary, synchronous replication is beneficial. However, this may cause the primary to hang if the transactions are not committed to the replica.
Table-level replication can be achieved using external open source tools like Slony, Bucardo, Londiste, and RubyRep, all of which utilize trigger-based replication. Additionally, PostgreSQL supports logical replication, which performs table-level replication using WAL records and alleviates the complexity of trigger-based replication. Initially supported by an extension called pglogical, logical replication has been part of the PostgreSQL core since Version 10.
MySQL
MySQL supports a primary-replica and primary-to-multiple-replicas mechanism, ensuring that data changes are replicated from a primary to a replica database via SQL. Replication is asynchronous, which can pose challenges in terms of performance and scalability.
A key advantage of MySQL replication is that replicas are not read-only; if an application fails over to a replica when a primary database crashes, the replica can consume both reads and writes, ensuring seamless application operation. However, DBAs must ensure that a replica exits replica mode and that all changes are reverse-replicated back to the primary, which can be slow when dealing with long-running SQLs.
Views
MySQL supports views, with a limitation that the number of tables used by the SQLs within the view is capped at 61. Views function as virtual tables that do not store data physically, and MySQL does not support materialized views. Views created with simple SQLs can be updated, while those created with complex SQLs cannot.
PostgreSQL supports views that operate similarly to those in MySQL. Simple SQL-constructed views can be updated, whereas complex SQL-constructed views cannot. However, there is a workaround to update complex views using RULES. Furthermore, PostgreSQL supports Materialized Views, which can be refreshed and indexed if the data needs to be stored physically.
Triggers
MySQL supports triggers for ‘AFTER’ and ‘BEFORE’ events on ‘INSERT’, ‘UPDATE’, and ‘DELETE’ statements. However, triggers in MySQL cannot execute dynamic SQL statements or stored procedures. This limitation can affect the flexibility required for handling more complex database operations.
PostgreSQL offers more advanced trigger capabilities, supporting ‘AFTER’, ‘BEFORE’, and ‘INSTEAD OF’ triggers for ‘INSERT’, ‘UPDATE’, and ‘DELETE’ events. This dynamic execution capability makes PostgreSQL triggers more versatile, enabling the efficient handling of complex SQL operations through the use of functions.
CREATE TRIGGER audit
AFTER INSERT OR UPDATE OR DELETE ON employee
FOR EACH ROW EXECUTE FUNCTION employee_audit_func();
Stored Procedures
Stored procedures are a crucial component of databases, addressing complex data extraction requirements, and developers often incorporate stored procedures into their database development processes. Both MySQL and PostgreSQL support stored procedures, but MySQL only supports standard SQL syntaxes, while PostgreSQL offers more sophisticated procedures.
PostgreSQL implements stored procedures as functions with a ‘RETURN VOID’ clause, a feature favored by developers for its support of multiple programming languages not available in MySQL, such as Ruby, Perl (PL/Perl), Python (PL/Python), PL/PgSQL, SQL, and JavaScript.
Storage
Data storage is a critical aspect of any database system. PostgreSQL and MySQL provide several options for storing data, which involves saving physical database objects like Tables and Indexes to a disk. This section explores two types of storage options: common storage and pluggable storage.
PostgreSQL employs a common storage mechanism known as tablespaces, which accommodates physical objects such as Tables, Indexes, and Materialized Views. Tablespaces enable the efficient distribution of I/O by grouping and storing objects across multiple physical locations. However, PostgreSQL does not currently support pluggable storage engines, though this feature is anticipated in future releases.
MySQL features a tablespaces option within its InnoDB engine, akin to PostgreSQL, allowing DBAs to group and store physical objects, thus enhancing I/O distribution. Additionally, MySQL offers support for pluggable storage engines, catering to specific storage needs for various applications like OLTP and Data Warehousing. This capability is one of MySQL’s most significant advantages, as the pluggable storage feature is enabled through the installation of plugins. Although configuring pluggable storage can be complicated, applications remain unaffected by these complexities.
Analytical Functions
Analytical functions perform aggregation on sets of rows. There are two primary types of analytical functions: window functions and aggregate functions. Aggregate functions provide a single value per set of rows (such as SUM, AVG, MIN, MAX), while window functions return a value for each row. Both MySQL and PostgreSQL support various analytical functions. MySQL has since introduced some window functions in Version 8.0, whereas PostgreSQL has long supported a wide range of them, such as:
Function | Description |
---|---|
CUME_DIST | Returns the relative rank of the current row. |
DENSE_RANK | Ranks the current row within its partition without gaps. |
FIRST_VALUE | Returns a value evaluated against the first row within its partition. |
LAG | Returns a value evaluated at the row that is at a specified physical offset row before the current row within the partition. |
LAST_VALUE | Returns a value evaluated against the last row within its partition. |
LEAD | Returns a value evaluated at the row that is offset rows after the current row within the partition. |
NTILE | Divides rows in a partition as equally as possible and assigns each row an integer starting from 1 to the argument value. |
NTH_VALUE | Returns a value evaluated against the nth row in an ordered partition. |
PERCENT_RANK | Returns the relative rank of the current row (rank-1) / (total rows-1). |
RANK | Ranks the current row within its partition with gaps. |
ROW_NUMBER | Numbers the current row within its partition, starting from 1. |
MySQL supports almost all of the same window functions as PostgreSQL, with the following limitations:
- Window functions cannot be used as part of ‘UPDATE’ or ‘DELETE’ statements.
- ‘DISTINCT’ is not supported with window functions.
- ‘NESTED’ window functions are not supported.
Administration and GUI Tools
MySQL databases can be accessed remotely using a variety of GUI tools such as Oracle’s SQL Developer, MySQL Workbench, DBeaver, and OmniDB. For monitoring the performance and health of a MySQL database, popular tools include Nagios, Cacti, and Zabbix.
PostgreSQL, similarly, can be GUI-managed using Oracle’s SQL Developer, pgAdmin, OmniDB, and DBeaver. To monitor PostgreSQL’s performance and health, tools like Nagios, Zabbix, and Cacti are also widely used.
Performance
MySQL
Optimizing MySQL database performance can be challenging due to its limited options and lack of support for many index types. Without full SQL compliance, crafting efficient and high-performing SQL queries becomes difficult. MySQL is also not ideal for handling large volumes of data. While tablespaces exist to distribute data across multiple disks, they are restricted to the InnoDB engine and cannot accommodate table partitions. To expedite simple queries that access tables, creating B-Tree indexes can be beneficial.
PostgreSQL
PostgreSQL is highly adaptable for various workloads, including OLTP, OLAP, and data warehouse. It fully complies with SQL standards, allowing for the writing of efficient queries and PL/PgSQL programs. Its support for a wide array of indexes — such as B-Tree, Bitmap, Partial, and Full-Text — enhances overall performance. Online re-indexing and table re-organization can help to remove data bloats effectively. PostgreSQL also provides multiple configuration options for memory allocation, and partitioned tables can be distributed across multiple tablespaces to efficiently balance disk I/O.
Security
For enterprises, database security plays a vital role in protecting data from unauthorized access. Secure access is implemented at different levels within the database, including the object-level and the connection-level.
MySQL
MySQL manages database, object, and connection access through ROLES and PRIVILEGES. Each user must be granted a connection privilege using an SQL command for every individual IP address they connect from, or privileges can be granted all at once across multiple IP addresses within a subnet.
An example command to grant all privileges on the database “testdb” to the user “testuser” from the IP “192.168.1.1” would look like this:
GRANT ALL PRIVILEGES ON testdb.* TO 'testuser'@'192.168.1.1' IDENTIFIED BY 'newpassword';
If the user is connecting from all IPs within the 192.168.1 subnet, the command would be:
GRANT ALL PRIVILEGES ON testdb.* TO 'testuser'@'192.168.1.*' IDENTIFIED BY 'newpassword';
When granting privileges, a password must be specified, otherwise the user will not be able to connect.
Additionally, MySQL supports SSL-based connections over the network and provides security through SE-Linux modules. Integration with external authentication systems, such as lightweight directory access protocol (LDAP) and privileged access management (PAM), is available within the MySQL enterprise edition.
PostgreSQL
PostgreSQL enables access to database objects and data using ROLES and PRIVILEGES defined through ‘GRANT’ commands. Connection authentication is managed more simply via a ‘pg_hba.conf’ authentication file, which lists IP addresses, usernames, and access types, offering a more straightforward and dependable approach. A sample entry from a ‘pg_hba.conf’ file might look like this:
host database user address auth-method [md5 or trust or reject]
PostgreSQL’s open source version supports SSL-based connections and can be integrated with external authentication systems, including LDAP, Kerberos, and PAM, making it both efficient and reliable.
Extensibility
PostgreSQL is regarded as a highly extensible tool since it supports various advanced data types that one can’t find in MySQL. This would include network address types, native UUID, geometric/GIS, JSON which can be indexed, and timezone-aware timestamps. If this didn’t make PostgreSQL a clear winner for this round, you could add your operators, data types, and index types.
So, if your application is tackling unstructured data or any of the unique data types it has available, PostgreSQL might be the better suitor. However, if you only deal with basic numeric and character data types, both databases should work fine.
Support & Community
Both PostgreSQL and MySQL have helpful communities to provide support to users.
PostgreSQL boasts a large community of volunteers who offer free advice to users through mailing lists and IRC. On top of this, you can even purchase paid support through third-party providers. You can even troubleshoot by going through the various helpful PostgreSQL books and manuals on the market.
MySQL too has a large volunteer community that devotes its time to help you out with free recommendations and support. You can avail this kind of support on the third-party and MySQL websites. On top of the free community support, Oracle also offers 24/7 paid support with the commercial versions of all its products. Like PostgreSQL, you can also carry out your troubleshooting by delving into the numerous free and helpful MySQL guides, books, and tutorials.
Which Should You Choose?
To summarize the discussion, choosing between the two databases isn’t always straightforward. Since there are no wrong answers here, it boils down to context.
If you’re looking for a feature-rich database that can smoothly tackle voluminous databases and complex queries while allowing you to grow any application to enterprise scope, you should go with PostgreSQL.
On the other hand, if you’re a beginner looking for a database that’s easier to manage and set up while still being reliable, fast, and well understood, you might try MySQL.
If you simply can’t decide, one option is to take them both for test drives before making your final decision.