ReviewsPostgreSQL vs MySQL: Compare Database Management Systems

PostgreSQL vs MySQL: Compare Database Management Systems

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MySQL and PostgreSQL are the top two open-source relational database management systems (RDBMS), long proven to be highly reliable and scalable. In this article, we explore PostgreSQL vs MySQL, and the differences between them.

Read more: Best SQL Server Monitoring & Performance Tools 2022

What Is PostgreSQL?

PostgreSQL is an advanced open-source RDBMS developed by PostgreSQL Global Development Group. Initially released on July 8, 1996, it was started as part of the POSTGRES project in 1986 at the University of California, Berkeley.

PostgreSQL is an enterprise-class relational database that allows both relational and non-relational querying. It supports procedural languages, such as:

  • PL/pgSQL
  • PL/Python
  • PL/Tcl
  • PL/Perl

It also supports non-standard procedural languages, such as Java, .NET, Go, Ruby, C, C++, and ODBC.

PostgreSQL is available for these operating systems:

  • macOS
  • Windows
  • Linux
  • FreeBSD
  • OpenBSD
  • NetBSD
  • AIX
  • HP-UX
  • Solaris
  • UnixWare, as well as most other Unix-like systems

Moreover, PostgreSQL is the default database for Apple’s macOS Server.

The use of the SQL language in PostgreSQL makes it extendable and standards-compliant. PostgreSQL provides a large number of operators and functions for built-in data types. To achieve optimum performance, PostgreSQL server administration is capable of many necessary optimization tasks: software installation, server set-up and configuration, user and database management, and maintenance tasks.

PostgreSQL is one of the most stable database management systems and is commonly used as the primary data store or warehouse for website, geospatial, and analytics applications.

Read more: What Is PostgreSQL? Open-Source Database System

What Is MySQL?

MySQL is an open-source RDBMS developed by Oracle Corporation. Originally developed by Swedish company MySQL AB, MySQL was initially released on May 23, 1995.

MySQL works on many system platforms, including Linux, Windows, macOS, FreeBSD, AIX, HP-UX, ArcaOS, BSDi, eComStation, OpenBSD, IBM i, IRIX, Oracle Solaris, NetBSD, Novell NetWare, OpenSolaris, OS/2 Warp, Sanos QNX, Symbian, Tru64, SunOS, SCO OpenServer, and SCO UnixWare.

MySQL is one of the most stable database management systems, and some cloud platforms offer it “as a service.” Cloud-based MySQL services include:

  • Oracle MySQL Cloud Service
  • Amazon Relational Database Service
  • Azure Database for MySQL
  • HP Converged Cloud
  • Rackspace
  • Jelastic
  • Heroku

MySQL also offers two different editions, MySQL Community Edition and MySQL Enterprise Edition.

PostgreSQL vs MySQL: What Are the Differences?

PostgreSQL and MySQL are both free, open-source RDBMSs. But there are several differences between them.

Best forConcurrent write operationsRead-heavy processes
DBMS typeObject-based relationalRelational-based
ReplicationSynchronousOne-way synchronous
SecurityNative SSL supportTLS support
Object statisticVery goodFairly good
ACID complianceCompleteLimited
SQL compliantLargelyPartially
Join capabilitiesGoodLimited
MVCC supportFullLimited
Partial, bitmap, and
expression indices
SupportedNot supported
CASCADE optionSupportedNot supported
Written inCC, C++
LicensePostgreSQL LicenseGPLv2 or proprietary


PostgreSQL and MySQL are both well-known and widely used database management systems; they have comparable performance in real-world scenarios.

PostgreSQL Performance

PostgreSQL supports a variety of performance optimizations that are available for commercial solutions including geospatial data support, concurrency without reading locks, and so on. PostgreSQL is widely used in large systems; PostgreSQL is most advantageous for systems where complex queries need to be executed.

PostgreSQL performs well with business intelligence (BI) applications and is better suited for data analysis and data warehousing applications needing fast speeds to read/write. For this reason, it also works well in OLTP/OLAP systems.

Read more: SQL Performance Tuning Best Practices

MySQL Performance

MySQL is common and widely chosen as a web-based database for straightforward data transactions. The overall performance is good, but MySQL underperforms for heavy loads or complex queries.

MySQL performs well and is reliable with some BI applications, especially for read-heavy applications. It also works well in OLAP/OLTP systems when needed for fast read speeds. MySQL and InnoDB together provide very good read/write speeds for OLTP scenarios, and work well with high concurrency scenarios.

Data Types

MySQL and PostgreSQL vastly differ in the types of data they support, and PostgreSQL tends to have the advantage here.

PostgreSQL Data Types

PostgreSQL can store both structured and unstructured data types in a single product. It supports most of the data types, such as numeric, monetary, character, binary, date/time, boolean, enumerated, geometric, network address, BitString, text search, UUID, XML, JSON, arrays, composite, ranges, domain, object identifier, pg_lsn, and pseudo.

MySQL Data Types

MySQL supports all SQL-standard types of data in several categories including numeric, date and time, character and byte string, and spatial. MySQL implements spatial extensions as a subset of the SQL with geometry types environment, following the Open Geospatial Consortium (OGC) specification.


MySQL has a reputation as an extremely fast database for read-heavy workloads, and it is great at read-heavy processes. But when mixed with write operations, MySQL can be the cost of concurrency.

On other hand, PostgreSQL advertises itself as “the most advanced open-source relational database in the world.” PostgreSQL was built to be standards-compliant, feature-rich, and extendable, and it is great at concurrent write operations.

Organizations could choose MySQL for read-heavy operations and PostgreSQL for concurrent write operations. However, based on overall performance, PostgreSQL should be the first choice.

Read more: SQL Query Optimization Best Practices

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