In the world of open-source relational database management systems, the undisputed champions vying for the top spot are MySQL and PostgreSQL. These relational DBMSs are renowned for both their resilience and the fact that they scale with ease, so let’s see how they measure up against each other.
PostgreSQL Global Development Group developed this state-of-the-art non-proprietary RDBMS, releasing it in the summer of 1996, but we can trace its lineage back to 1986 and Berkeley University in California, where it began life as part of a project called POSTGRES.
In its present incarnation, it’s an enterprise-level relational database that can handle two types of querying — relational and non-relational. Procedural languages are supported too, and these include:
but so are alternative examples, like Java, .NET, Go, Ruby, C, C++, and ODBC.
PostgreSQL gets on like a house on fire with a broad selection of OSs:
- UnixWare (and pretty much all the other Unix-like systems you could name, too.)
PostgreSQL is the macOS Server standard database. You can extend it with ease and it’s compliant with most standards.
In terms of server administration, PostgreSQL is a jack of all trades that is comfortable handling a wide range of obligatory optimization duties, including installing new software packages, setting up and configuring servers, managing databases and those who use them, not to mention maintenance tasks. It also offers a significant selection of operators and functions for handling built-in data types.
In terms of stability, PostgreSQL is recognized for its resilience, which is why it’s trusted as the primary data repository for so many website, geospatial, and analytics apps.
MySQL commenced its existence as a project of MySQL AB of Sweden and further development was carried out by Oracle Corporation. It’s another non-proprietary relational database management system that first hit the market in 1995.
This version is compatible with a wide variety of platforms, like 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 rocksteady in terms of stability, so much so that some cloud platforms offer it “aaS” (as a service), so you can access it via:
- Oracle MySQL Cloud Service
- Amazon Relational Database Service
- Azure Database for MySQL
- HP Converged Cloud
PostgreSQL vs MySQL: Comparison
You don’t need to part with a single penny for PostgreSQL and MySQL. They are both free and non-proprietary, but it’s good to be aware of their key differentiators.
|DBMS type||Object-based relational||Relational|
|Security||Native SSL support||TLS support|
|Object statistic||Very good||Fairly good|
|Partial, bitmap, and expression indices||Supported||Not supported|
|CASCADE option||Supported||Not supported|
|Written in||C||C, C++|
|License||PostgreSQL License||GPLv2 or proprietary|
MySQL vs PostgreSQL: Performance
PostgreSQL and MySQL enjoy wide use and they perform at comparable levels in everyday situations.
Performance of PostgreSQL
PostgreSQL supports a variety of performance enhancements for commercial apps like geospatial data support, concurrency without reading locks, and more. PostgreSQL enjoys broad employment in large-scale systems and provides the most benefits in those that need to undertake complicated requests.
PostgreSQL is best suited to chewing through business intelligence duties, data analysis and serving data warehousing apps that require lightning-fast read/rights. These abilities are why its performance with OLTP/OLAP systems is so good.
MySQL has managed to achieve widespread adoption and serves as an online database for less complicated data transactions. It is generally considered to be a solid performer, but where MySQL doesn’t fare so well is when it’s placed under more demanding workloads or made to wade through complicated queries.
MySQL shows decent performance and reliability with some business intelligence applications, particularly the more read-dominant ones. It also performs admirably with OLAP/OLTP systems where quick reads are of prime concern. When MySQL and InnoDB are used in conjunction they offer superlative read/write speeds for OLTP situations and where high concurrency is indispensable.
MySQL and PostgreSQL show considerable differences in the types of data they are able to take care of, and PostgreSQL pulls ahead in this regard.
PostgreSQL Data Types
PostgreSQL is able to hold both structured and unstructured data types in one product. It accommodates most clients, 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 is fine with all SQL-standard types of data in a range of categories that include numeric, date and time, character and byte string, and spatial. MySQL carries out spatial extensions as a subset of the SQL using flat coordinates that follow the Open Geospatial Consortium (OGC) standard.
MySQL is renowned as a very fast and capable database that favours and performs well with read-dominant workloads and processes. When right operations are added into the mix, however, MySQL’s ability to handle concurrency takes a significant hit.
In contrast, PostgreSQL’s marketing promotes it as “the most advanced open-source relational database in the world.” It was created with wide standards compliance in mind, offers a great selection of features and ample extendibility. It also won’t struggle with concurrency when tasked with a predominance of write operations.
With these factors in mind, it might seem sensible to give the dominant operations to MySQL and the concurrent write operations to PostgreSQL, but if all-around performance is your goal, PostgreSQL should be your winner.