Introduction:

‍In this article, we will be looking at and discussing the differences between the two most popular open-source relational databases: MySQL vs Postgres. We will examine their advantages and disadvantages, and how they work. We will also talk about their features and how they can be used in different scenarios.

What is Postgres?

Postgres is an open-source object-relational database system popularly known as Postgres, a powerful database management system designed to handle a range of workloads from single machines to large web-facing applications. It is the most advanced open-source database available, with a wide range of features including triggers, rules, stored procedures, and more. This database supports a wide range of programming languages, including C, C++, Java, PHP, Perl, Python, and more giving flexibility to its users. It is also highly extensible and can be easily customized to fit specific needs offering a wide range of additional attributes such as replication, and clustering. Many organizations, including banks, universities, and government agencies, use Postgres as it is an excellent choice for a wide range of applications and is sure to continue to be a popular choice for years to come.

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What is MySQL Database?

MySQL database is an open-source relational database management system (RDBMS) that uses Structured Query Language (SQL) to add, access, and manage data. It is one of the most popular database systems used in web applications and online services, powering some of the most widely used websites and applications on the internet. It is designed for scalability and can handle enormous datasets with ease. It is typically used in combination with a web scriptings language such as PHP, Perl, or Python. This combination allows developers to quickly build web applications that can interact with databases. MySQL also supports a variety of storage engines, allowing developers to choose the one that best suits their application's needs. MySQL is easy to install and use, making it a popular choice for many applications, especially for small and medium-sized organizations. 

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MySQL and Postgres are two of the most favored open-source databases that are used by developers and businesses across the globe. Though both databases provide powerful options for data storage and management, there are some key differences between the two that should be taken into consideration when making a decision about which one to use. Let us discuss the key distinctions between MySQL and Postgres in this section.

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MySQL vs Postgres: 15 Major Differences 

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1. MySQL vs Postgres: Architecture

Postgres is an object-relational database management system (ORDBMS) that uses a more complex architecture than MySQL. It has more advanced features than MySQL, including the ability to store and manipulate complex data types such as arrays, user-defined types, and geometric data. It also supports advanced programming languages such as PL/pgSQL, which allows developers to write stored procedures and functions. 

MySQL is a relational database management system (RDBMS) that uses a simpler architecture than Postgres. It does not have the same advanced features as Postgres, such as support for complex data types or support for advanced programming languages like PL/pgSQL but still is one of the most used databases due to its simple and efficient architecture.

MySQL is considered to be a popular choice for small to medium-sized businesses and is known for its ease of use and simple setup. Postgres, on the other hand, is widely used in enterprise-level applications and is considered to be a more robust and feature-rich database management and operating system.

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2. MySQL vs Postgres: Speed

The speed difference between Postgres and MySQL largely comes down to the way each database is designed. 

Postgres is a highly customizable relational database system with a powerful query language and a wide range of features. It is designed to be highly extensible, allowing developers to customize the database to fit their needs. This flexibility can come with a cost in terms of database performance, however, as Postgres has to consider a variety of factors when executing a query. 

MySQL, on the other hand, is designed to be simpler and more streamlined. It is optimized for speed, with a focus on keeping queries as simple as possible. This makes MySQL faster and more efficient at executing certain types of queries, particularly those involving many records. The speed difference between Postgres and MySQL can also be attributed to the type of data that each database is optimized for. 

Postgres is generally considered to be faster for complex queries and MySQL is designed for executing simpler queries efficiently.

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3. MySQL vs Postgres: Database Performance

Postgres is well known for its performance when it comes to executing large queries with complex transactions. It also has a fast query optimizer which is able to create an execution plan for the given query. Additionally, Postgres provides several features like indexing, materialized views, and parallel query execution that can help improve query performance.

MySQL is well known for its performance when it comes to executing simple queries and transactions. Additionally, MySQL provides several features like query caching, table partitioning, and indexing which can help enhance query performance.

The performance difference between Postgres and the MySQL databases is largely due to the differences in architecture and design. Overall, Postgres is better suited for complex, high-traffic applications that require advanced database features only, while MySQL is better suited for smaller applications with less traffic.

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4. MySQL vs Postgres: Scalability

Postgres is generally considered to be more scalable than MySQL. This is due to the fact that Postgres offers several features that are designed to improve scalability, such as asynchronous replication, advanced locking, and row-level locking. Postgres also provides a wide range of data types and supports a variety of programming languages, which allows developers to create more complex applications. 

MySQL, on the other hand, has limited scaling capabilities mainly due to the lack of some of the advanced features that Postgres offers. For instance, MySQL does not support asynchronous replication and advanced locking. Additionally, MySQL only supports a limited number of data types and programming languages, which can limit the complexity of applications. Furthermore, MySQL does not offer row-level locking, which can cause performance issues when scaling out.

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5. MySQL vs Postgres: Security

Postgres uses an authentication and access control system that is considered to be more secure than other MySQL databases depending on the business needs. Along with authenticating using a username and a password before accessing the database Postgres also supports row-level security, which allows users to set restrictions on which data can be viewed or modified by certain users. Additionally, it supports the encryption of sensitive data preventing unauthorized data access.

MySQL is a secure and reliable database management system that provides a variety of security mechanisms to protect your data from unauthorized access. These include authentication, encryption, access control, and role-based access control. Authentication is used to ensure that only authorized users have access to the database. Encryption is used to ensure that the data is not readable without the proper credentials. Access control is used to control who can access the database and what they can do with the data. Finally, role-based access control is used to ensure that each user has the right level of access to the data they need. With these features, the MySQL database operating system is able to provide a secure and reliable environment for your data.

Overall, Postgres and MySQL provide their users with almost the same security features and have more advanced user authentication,, access control, and encryption capabilities that make them a more secure choice for storing sensitive data.

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6. MySQL vs Postgres: Indexes

Indexes in Postgres and MySQL are similar in that they are both used to quickly retrieve data from a database. However, there are some key differences between the two. 

Postgres supports a wider range of index types as compared with MySQL. It supports B-tree, GiST, GIN, Hash, BRIN, and SP-GiST indexes allowing for more complex index combinations (e.g. multi-column indexes). It gives more flexibility to its users in the way indexes are used. For example, Postgres allows for the creation of partial indexes, which can be used to index only a portion of a table's rows. It supports more advanced features such as concurrent index creation, which allows for the creation of indexes without locking the entire table.

MySQL supports several different index types, including B-tree, and hash indexes, full-text, and spatial indexes. B-tree indexes are used to quickly locate data without having to search through every row of a table. Hash indexes are used to quickly locate exact matches. Full-text indexes are used to search text columns for words and phrases. Spatial indexes are used to both store data and search for geographical data, such as points or shapes on a map.

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Overall, Postgres and MySQL both offer the same indexing capabilities but before selecting a database users should consider the specific needs of the application and the required use case should also be kept in mind.

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7. MySQL vs Postgres: Data Types

In Postgres, all data types are classified as either a primitive or a composite data type. Primitive data types are the most basic data types, like boolean, integer, and text. The composite data types are composed of multiple primitive data types, like arrays, enumerations, and ranges. It also supports custom data types, called domains, which are made up of both primitive and composite data types. 

In MySQL, all data types are classified as either a numeric type, a character type, a temporal type, or a spatial type. Numeric types include integer, float, and decimal, while character types include char, varchar, and text. Temporal types include the date, time, and timestamp, while spatial types include point, line, and polygon. MySQL also supports custom data types called ENUMs and SETs, which are made up of multiple character types. 

Overall, Postgres has a more comprehensive selection of data types compared to MySQL, although both databases support the basic data types. Postgres also has the advantage of creating custom data types, which can be beneficial for complex data requirements.

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8. MySQL vs Postgres: Replication

Postgres and MySQL are both popular open-source relational databases, and each has its own set of features and replication capabilities. One of the main differences between the two databases is in the way they handle replication. 

Postgres supports both synchronous and asynchronous replication, meaning that changes can be made to the master database and then replicated to a replica server. Synchronous replication ensures that the data is consistent across all servers, while asynchronous replication allows for potentially faster writes at the cost of potential data inconsistency. 

MySQL, on the other hand, supports only asynchronous replication. This means that changes are sent directly to the replica server without any guarantee of consistency. As a result, there is a higher risk of data corruption and inconsistency when using MySQL replication. It also supports various types of replication including: statement-based, and row-based being the two core replication techniques, and also consists of a third mixed replication technique.

Overall, Postgres has more robust replication capabilities than MySQL, but MySQL has a statement-based and row-based replication technique giving flexibility to users making both databases a good choice for applications that require consistent and reliable replication.

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9. MySQL vs Postgres: Triggers 

Triggers are a type of stored procedure that is automatically executed by the database engine in response to an event like insert, update, or delete. They are used to maintain the integrity of the data in the database and to automate certain tasks. 

The main difference between Postgres and MySQL triggers is the type of triggers that each supports. Postgres supports row-level, statement-level, and event-level triggers while MySQL only supports row-level triggers. 

Postgres supports BEFORE, AFTER and INSTEAD-OF triggers while MySQL only supports AFTER triggers. Postgres also supports using PL/pgSQL, an advanced programming language designed specifically for Postgres, while MySQL supports the use of SQL.

In general, Postgres offers more sophisticated and powerful trigger capabilities including control transaction handling ability than MySQL. 

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10. MySQL vs Postgres: Storage engines

Postgres and MySQL both use storage engines to manage how data is stored, retrieved, and manipulated. The main difference between the two is that while Postgres uses its own storage engine, called Postgres, MySQL uses a variety of storage engines, including InnoDB, MyISAM, Memory, Archive, and CSV. Postgres's default storage engine is highly customizable, allowing users to tweak settings to optimize database performance. It also offers features such as transactions and MVCC (Multi-Version Concurrency Control) for greater data integrity. Postgres also allows for the use of user-defined functions and stored procedures, which can be used to automate and optimize various tasks. MySQL's storage engines are optimized for specific use cases, such as MyISAM for read-heavy applications and InnoDB for write-heavy applications.

Postgres offers a customizable storage engine, while MySQL offers a variety of optimized storage engines. Each storage engine offers different features and benefits, so selecting the right storage engine for the job is important based on the specific user needs.

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11. MySQL vs Postgres: Full-text search

Full-text search is a powerful feature of relational databases that enables users to quickly search large volumes of text-based data for specific words or phrases. 

In Postgres and MySQL, full-text search is implemented differently due to the differences in the underlying database architectures. 

Postgres uses a native full-text search feature to enable users to quickly search through large text fields. Postgres's full-text search is based on a vector space model, which enables it to perform complex searches and to rank results by relevance. The full-text search feature in Postgres also allows users to specify language-specific dictionaries, which can be used to optimize searches for a particular language. 

MySQL, on the other hand, uses a combination of LIKE and REGEXP operators to implement a limited form of full-text search. The LIKE and REGEXP operators enable users to perform basic searches, but they cannot be used to rank search results by relevance. 

Overall, Postgres's native vector space model enables users to perform complex searches and rank results by relevance, while MySQL's LIKE and REGEXP operators are sufficient in their basic search capabilities.

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12. MySQL vs Postgres: Parallel query execution

Postgres and MySQL both support parallel query execution, but their implementations are quite different from one another.

In Postgres, parallel query execution is achieved by dividing a query into multiple parts, each of which is then executed in its own process. Each process then submits its results to a single coordinator process, which combines the results and returns them to the user. This approach is more efficient than running a single query, as it takes advantage of the resources of multiple CPUs to speed up execution. 

In contrast, MySQL uses a different approach to parallel query execution. It divides a query into multiple threads, each of which is executed in its own thread. Each thread then communicates with the coordinator thread, which combines the results and returns them to the user. This approach is less efficient than Postgres's approach, as it does not take advantage of multiple CPUs.

Overall, Postgres's parallel query execution is more efficient than MySQL's, as it takes advantage of the resources of multiple CPUs to speed up execution.

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13. MySQL vs Postgres: Materialised views

Postgres and MySQL are two popular relational database management systems (RDBMSs). Both support the concept of materialized views, which are database objects created to store the results of a query for faster access. However, there are some differences between the two implementations. 

In Postgres, materialized views are created using the CREATE MATERIALIZED VIEW statement. They are stored as separate objects in the database and are not automatically updated when the underlying data changes. This means that the materialized view must be manually refreshed when the underlying data is modified. Additionally, Postgres's materialized views can be indexed to speed up query performance. 

In MySQL, materialized views are created using the CREATE VIEW statement. Unlike Postgres, MySQL materialized views are automatically updated when the underlying data changes. This means that there is no need to manually refresh the materialized view. 

In Postgres, materialized views are stored as separate objects and must be manually refreshed, while MySQL has an upper hand on this as materialized views are automatically updated. 

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14. MySQL vs Postgres: Backup and recovery 

Postgres and MySQL are both popular open-source relational database management systems and both have their own strengths and weaknesses. When it comes to backup and recovery, Postgres and MySQL have some distinct differences. 

Postgres offers a variety of options for backing up and restoring data. The most basic is a full backup, which makes a copy of all the data in the database. It can also take incremental backups, which only back up the data that has changed since the last backup. It also has a hot backup feature, which allows the database to remain online while the backup is being taken and also offers the ability to restore from any point in time, which is useful in the event of data corruption. 

MySQL offers two primary methods for backing up and restoring data: mysqldump and physical backups. mysqldump takes a logical backup of the database, which includes all the data and the structure of the database. Physical backups are more complex and require the backup to be taken from the underlying storage system, such as a storage area network (SAN) or a cloud service like AWS. 

Overall, Postgres's ability to take incremental backups, perform hot backups, and restore from any point in time makes it a more robust choice for backing up and restoring data.

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15. MySQL vs Postgres: Community Support

Postgres and MySQL both offer community support for their respective database systems. 

Postgres has an active mailing list that lets users post questions and get responses from the community. MySQL has over 5.6 million installations and over 1.2 million active users, while Postgres has over 4 million installations and over 600,000 active users. Both communities are extremely active on Stack Overflow, with MySQL having over 62,000 questions and Postgres having over 44,000 questions. Additionally, both communities are active on GitHub, with MySQL having over 5,000 contributors and Postgres having over 1,500 contributors. 

With these digits, it's clear that both MySQL and Postgres have vibrant, supportive communities that are ready to help anyone out with any issues they might have. 

Conclusion: 

MySQL and Postgres are both popular database management systems that can be used to store and manage data for a wide variety of applications. Both offer a number of advantages, including scalability, reliability, and flexibility. However, when it comes to choosing between the two of them for a data project, the decision largely depends on the specific requirements of the project. 

Sprinkle Data is a great option for those looking for a cloud-based database solution for unifying their data. It is a fully managed data pipeline and analytics platform that helps users to unify data from MySQL, and Postgres and has support for over 100+ data sources, without the need to install, maintain, or manage any software.

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FAQS

Is Postgres faster than MySQL?

It depends on the use case. with MySQL it is generally considered faster for web applications, while Postgresql it is more powerful and feature-rich. The Postgresql database is typically faster for complex queries and data analysis, while MySQL is often faster with simpler queries.

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Is Postgres safer than MySQL? 

Postgres and MySQL are both secure, but Postgres has some additional security features that make it more secure. Postgres has a built-in auditing system along with that it also has a built-in system for encrypting data.

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Should I choose MySQL or Postgres? 

The best way to decide between MySQL and Postgres is to consider your specific requirements. MySQL is the most popular open-source relational database and is typically the best choice for smaller applications, while Postgres is better for high-volume applications and provides more advanced features. Ultimately, the best choice for you depends on your use case.

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Does Amazon use MySQL or Postgres? 

Amazon uses both MySQL and Postgres. Amazon Relational Database Service (RDS) also supports both MySQL and Postgres. 

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What are the disadvantages of Postgres? 

• Limited Windows Functionality: Postgres does not have as many features or robust support for Windows as other database systems. 
• Limited Commercial Support: As an open-source database system, Postgres has limited commercial support options compared to other proprietary database systems. 
• Poor Documentation: Postgres's documentation is sometimes lacking in comparison with other database systems.

Which big companies use Postgres? 

There are over 1,000 large companies and organizations that use Postgres, some of them are mentioned below: 

• Apple 
• Twitter 
• Spotify 
• Instagram 
• Yahoo
• Cisco 
• Amazon
• Uber
• Netflix

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