How can one trust the leading open source database engines such as PostgreSQL and MySQL, to deliver a performance and feature just like commercial database engines such as Oracle, SQL Servers, and DB2? They not just offer such great performances but they are enough to meet your needs. In this article, we are going to discuss in detail as to how PostgreSQL and MySQL stack up against each other.
The term, open source software, often confuses a lot of people. When we talk about commercial software, it means a specific company is going to hire manpower which develops a product and sell it to the general public. However, in the internet era, every possibility exists and open source software does not require any company. Some capable programmers gather and exchange their idea over the internet with each other and put a program on a single accessible place for everyone. In this way, programs get developed and once it is sufficiently functional, it goes public.
We will compare PostgreSQL and MySQL with each other. Often we relate them on the basis of speed, though their speed has gotten much faster as compared to their earlier versions, speed isn’t the only thing when it comes to choosing an open source database engine. The comparison will be on the basis of features rather than the speed.
Understanding the differences between traditional relational databases like PostgreSQL and MySQL and graph databases is crucial when considering database solutions. While PostgreSQL and MySQL are powerful open-source relational database systems that structure data into tables and are proficient in handling a vast range of data applications, they fundamentally differ from graph databases in their architecture and data representation.
Graph databases, on the other hand, are designed to store and navigate relationships in a more intuitive and performant way. They treat relationships between data points as equally important to the data itself. An open-source graph database leverages a graph structure with nodes, edges, and properties to represent and store data, which allows for high-performance queries on complex data. This structure is particularly advantageous for applications such as social networks, recommendation engines, and fraud detection, where relationships can be as significant as the data points themselves.
The distinction is not just in the way data is represented but also in how it is retrieved. SQL queries can become complex and less performant as the number and depth of relationships increase. In contrast, graph databases are optimized for such tasks, enabling them to execute deep relational queries more efficiently. Therefore, when considering an open-source database solution, it is important to understand the nature of your data and the relationships within it to choose the most appropriate database type for your needs.
This is one of the most popular database engines and is developed, distributed, supported, and maintained by Oracle Corporation. Being an open source it can be modified by anyone, but if you wish to buy a commercial license, then it is also possible. MySQL is considered to be fast, efficient, scalable, easy to use, and reliable. The database of MySQL is a client/server base. It comes with the support for different programs, libraries, admin tools, and API’s. MySQL has the ability to run on different OS’s. Different kinds of data types are supported including SQL statements and functions. MySQL is considered to be reliable for gigantic databases.
This open source database engine is a client/server relational database. It has many features such as it is object-relational, which means there is an inheritance between tables and classes and every table defines a class. Another feature is transaction processing, in which data is protected and simultaneously handle multiple users. Referential integrity is another feature in PostgreSQL which take care of primary and foreign key relation. In PostgreSQL, multiple procedural programming languages can also be used.
All the databases have the same core purpose: data storing. However, they differ from each other once we look for them on the basis of their performance and reliability. It is sometimes hard to differentiate, especially, from open source databases by knowing their description.
License: For MySQL, there are two options available in terms of the license, one is general public and the other one is commercial. In general public license, one can able to modify and share, whereas commercial license must be purchased to make their own database into commercial use. PostgreSQL can be used as a commercial product without sharing the code under the Berkeley License.
Data Storage: Many Many of the mechanisms are used in MySQL to store the data and InnoDB is the primary mechanism. On the other hand, Postgres storage system is the only mechanism to be used in PostgreSQL.
Data Integrity: Both open source database engines are ACID compliant. ‘I’ represents Isolation and there are four levels of Isolation: Repeatable Read, Read Committed, Read Uncommitted, and Serializable. PostgreSQL supports three levels: Repeatable Read, Read Committed, and Serializable. MySQL supports all the isolation levels.
SP’s and Triggers: Both MySQL and PostgreSQL supports triggers and stored procedures.
Indexes: MySQL and PostgreSQL supports these indexes: single column, multi column, unique key, and primary key.
Data Types: Ordinary data types are supported in both, but only in PostgreSQL that user can able to define their own data types.
Platform Support: MySQL and PostgreSQL both are supported on various operating systems like Windows, MacOSX, and Linux.
DB Interface Method: They both have native method for accessing the database and support ODBC and JDBC. Java, Perl, Python, PHP, C, and C++ are supported by both.
DB Authentication: MySQL stores authentication information into a table and the data from the table is compared to the credentials. PostgreSQL has support for the same kind of system along with others such as a local authentication system that is based on a UNIX password.
Backups: Both have the ability for backups and performing it without even shutting down. Both MySQL and PostgreSQL can recover from soft crashes and power failures. But they are not in the same level of backup as offered by commercial products.
Data Migration: Both have support to migrate from commercial DBMS.
In the following table, you can view the brief comparison between MySQL and PostgreSQL.
|License||OS and commercial||OS|
|Platforms||Windows, Linux, MacOS X||Windows, Linux, MacOS X|
|Data Storage||Mainly InnoDB||Postgres Storage System|
|Data Type Support||General||General and possibility for own definitions|
|Replication||Single-Master & Master-Slave||Single-Master & Master-Slave|
|ODBC & JDCB Support||Yes||Yes|
|Data Migration Tools||OS and commercial||OS and commercial|
|GUI Tools||OS and commercial||OS and commercial|
|Back Ups||Ability to recover from soft crashes and power failures||Ability to recover from soft crashes and power failures|
According to my observation and experience, PostgreSQL has all-round functions present in it. While MySQL is more user-friendly and easy to operate with a higher reputation and influence as compared to PostgreSQL. The good thing for both of these open source DBMS is that they are easy to try out by anyone and has a lot of freely available documentation which helps the user in learning the product. These open source may be optimal for one project whereas they might not work for another complex project. Why not take both out for a spin and check yourself whether they meet your demands or not?