Every website and application needs a way to access and process data, and this means being able to manage your database. Database management systems are sometimes conflated with databases, but in reality, they allow you to interact with a database and perform management tasks such as controlling access, writing data, and running queries.
Most database management tools use a relational database management system (RDBMS) to organize data, and most relational databases use structured query language (SQL) to process and query the data. RDBMSs use a table-oriented data model, in which the relation schema is defined by the name of the table and a set of attributes with fixed data types. While there are non-SQL data models available, the relational data model remains the first choice for most organizations worldwide.
The two most popular open source RDBMSs are MySQL, developed by Oracle, and PostgreSQL. When choosing which database management tool to use, organizations consider memory, reliability, and query response time, but they also consider compatibility issues and the level of support offered. For this reason, the popularity of a tool can be a good measure of accessibility and the size of the open source community.
Comparing MySQL and PostgreSQL
In the competition to dominate the world of software, each tool has its advantages. MySQL was the most popular open-source RDBMS for several years, powering some of the world’s largest websites like Facebook, Twitter, and Netflix. However, a recent study indicates that PostgreSQL now has the lead and is ranked at #4 in terms of overall database popularity. PostgreSQL is used, for example, by Apple, Cisco, and Skype.
So let’s take a look at why some organizations choose either MySQL or PostgreSQL.
MySQL is a robust yet affordable database management system. Most websites and web applications can work easily on MySQL, as it is flexible and relatively scalable. PostgreSQL, on the other hand, is an open-source object-relational DBMS and is considered the most advanced and powerful tool of its kind. It is also more SQL compliant and works well with complex database designs. PostgreSQL is highly extensible and is optimized for complex queries and concurrency, which means it can handle multiple tasks at the same time.
In terms of functionality, PostgreSQL offers more possibilities, but MySQL has in-memory capabilities. PostgreSQL has less efficient memory performance, as it forks a new process for every connection, and each process takes up about 10MB of memory. If your database has many connections, the memory can add up, so it is unsuited to simple read-heavy operations when compared with MySQL.
MySQL supports more languages, but PostgreSQL is compatible with more operating systems. While both databases support numeric, date and time, and string data types, PostgreSQL also supports geometric shapes, text searches, network addresses, and other exotic and custom data types.
Let’s take a look at how they differ in terms of data replication (storing data in more than one place). MySQL has one-way asynchronous replication, which involves a master server and slave servers. This allows you to replicate selected tables within your database. PostgreSQL has synchronous (2-safe) replication, which runs two database instances simultaneously, while the master database is synchronized with a slave database. This makes it more suitable for concurrent read-writes.
Otherwise, PostgreSQL queries are usually identical to MySQL queries.
As open source tools, both RDBMSs require support in terms of the open source community, and both have a large community that develops them and contributes tools and information on how to use them. However, development of MySQL appears to have stagnated, and the community can no longer react quickly to issues or implement changes. PostgreSQL, on the other hand, has strong community and third-party support.
Now let’s consider some of the downsides of each tool. MySQL is designed for speed and reliability, but this comes at the expense of full adherence to standard SQL. MySQL also has some issues with stability and clustering, and it doesn’t support full outer joins.
PostgreSQL is optimized for complex operations and concurrency and helps protect data integrity, but it is inefficient for read-heavy operations. It is also not suited for speed or simple setups. Unless you are dealing with massive databases and complex queries involving multiple CPUs, PostgreSQL could be overkill, consuming large amounts of memory.
PostgreSQL is better for an application with many users writing data to it simultaneously. It is also appropriate for large systems that need to authenticate date, or if you need your database to perform custom procedures. Otherwise, MySQL may be the better option for a project that only needs a database for simple data transactions.
Many organizations are choosing to migrate from legacy database management tools like MySQL, but there are not necessarily switching to NoSQL. Migration from Oracle to PostrgeSQL doesn’t have to be difficult, given that PostgreSQL is easily integrated with a wide range of tools, and it may be worthwhile if you want to shift to a more complex and customizable system.
While MySQL certainly has its uses, for a growing number of companies, PostgreSQL has the edge.
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