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title: "MySQL vs. PostgreSQL: How Do They Compare? | CoderPad"
description: "A database is a convenient tool that allows users to access information, maintain records, and apply commonly used operations, such as insertion, modification, deletion, and data organization. Learn about MySQL vs PostgreSQL, their features, advantages, and disadvantages. Finally, check out which one is the best choice"
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last_modified: "2026-04-15 16:20:49"
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# MySQL vs. PostgreSQL: How Do They Compare?

April 17, 2023 6 Minute Read [Development](https://coderpad.io/blog/development/)

A database is a convenient tool that allows users to access information, maintain records, and apply commonly used operations, such as insertion, modification, deletion, and data organization. Various databases for daily operations are available in the market, including relational, object-oriented, cloud, and self-driven databases.

[MySQL](https://www.oracle.com/mysql/what-is-mysql/) is an example of a relational database. It is open source, which means everyone may use it for free. MySQL, also known as My Structured Query Language, is one of the oldest database management systems (DBMSs) and uses row-and-column tables to store data.

On the other hand, we have [PostgreSQL](https://aws.amazon.com/rds/postgresql/what-is-postgresql/). It is a compelling and open-source DBMS introduced on January 29, 1996. [PostgreSQL](https://coderpad.io/blog/development/sqlalchemy-with-postgresql/) works on widely used operating systems, such as Linux, Unix, Windows, and Mac OS.

In this article, we will discuss the features of both [databases](https://coderpad.io/resources/docs/interview/databases/) and outline their respective advantages and disadvantages. Afterward, we will compare both databases against some critical factors. By the end of this article, you will understand which database is better for your use case.

## MySQL Database

### Features of MySQL

- MySQL stores data and information and efficiently manages memory using [CRUD](https://www.freecodecamp.org/news/crud-operations-explained/) operations. Storing information is the primary feature of MySQL.
- MySQL is an open-source relational DBMS, which means anyone can download it from the official website and modify the code according to their needs.
- MySQL supports [General Public License (GPL)](https://www.gnu.org/licenses/gpl-3.0.en.html) guidelines, which state what can be done with the application and what is prohibited.
- It supports several data types, such as INT, CHAR, VARCHAR, DOUBLE, etc.
- It supports client-server architecture. The server often comes with client utility programs as well.

### Advantages

- Scalability: MySQL handles a vast amount of data. Furthermore, owing to multithreading support, it structures this data in almost 50 million rows. The default size of a file in MySQL is 4 GB, but this can be extended to 8 TB.
- Speed: It is considered one of the fastest DBMSs.
- Compatibility: It is compatible with most operating systems, such as Windows, Linux, and Unix.
- High flexibility: It supports widely used embedded applications. This is what makes MySQL a highly flexible DBMS.
- Easy availability: MySQL is open-source and free-to-use software. One does not need to pay anything to use and implement this database to their code.
- Secured: It comprises various highly embedded algorithms, which enhances this DBMS’s trustworthiness regarding data security.
- Efficiency in memory management: MySQL manages data memory so well that it only needs low-grade maintenance for memory management and uses what it needs efficiently.
- Better productivity: It uses tools like views, triggers, and joins that allow the development team to achieve higher performance with better productivity.
- Easy UI support: MySQL Workbench is a database tool that fully supports a graphical user interface. It consists of data development, management, and many other administrative agencies that make it easy for users to understand the data and the database’s internal workflow.
- Platform independency: Because it is compatible with most operating systems, it is inherently platform-independent.

### Disadvantages

- MySQL is usually preferred for small databases, as large database sizes are not supported.
- MySQL does not support procedures like role, store, and commit.
- MySQL does not support more than 4,096 columns in a single table.
- Some of its stored procedures are not developed for high-end business logic.
- MySQL does not handle data transactions well, which can introduce big issues like memory leakage, slow performance, or even data corruption.

## PostgreSQL Database

### Features of PostgreSQL

- PostgreSQL is also an open-source database system.
- It combines the object-relational architecture of DBMSs.
- It supports most [SQL standards](https://coderpad.io/blog/development/sql-functions-and-techniques-every-data-person-should-know/), such as views, triggers, transactions, complex SQL queries, hot standby, and foreign keys.
- It also supports different data formats, such as images, videos, sounds, etc.
- It can be used to develop different products and services; additionally, built-in [fault tolerance](https://www.2ndquadrant.com/en/blog/evolution-of-fault-tolerance-in-postgresql/) increases data integrity for any use case you are working on.

### Advantages

- Low maintenance: PostgreSQL does not need much maintenance because it utilizes write-ahead logging. This means that PostgreSQL can replay changes when a system does not switch off correctly.
- Easy to use: It is so easy to use that new users do not need prior knowledge or training.
- Free to use: It is free-to-use software.
- Large community: It has extensive community support, so if any doubt or issue arises during usage or development, users can quickly check to see if there are solutions to their problem already published on the internet.
- Supports ACID: It supports ACID: atomicity, consistency, isolation, and durability. These four properties are essential when working on crucial and sensitive data.
- User-defined data types: PostgreSQL supports user-defined data types using commands like CREATE DOMAIN and CREATE TYPE.

### Disadvantages

- The architecture of PostgreSQL separates all services from each other. This leads to more memory utilization.
- In terms of performance, PostgreSQL is not a sound DBMS.
- The speed of this DBMS is not very practical or attractive.
- It can become complex to work with.
- The installation process is not easy for beginners.

## MySQL vs. PostgreSQL

Now, let’s see a comparison between MySQL and PostgreSQL based on the features of an ideal DBMS.

S. No | Key Factors | MySQL | PostgreSQL
1. | Open-source application | Yes | Yes
2. | Security | Less secure than PostgreSQL | Advanced security tools
3. | ACID support | Only during [INNO DB](https://dev.mysql.com/doc/refman/5.6/en/innodb-introduction.html) and [NDB clusters](https://dev.mysql.com/doc/refman/8.0/en/mysql-cluster.html) | Fully supported
4. | CASCADE support | Yes | Yes
5. | GUI tools | MySQL Workbench | PG Admin
6. | Speed and complexity | Faster and easier | Slower and more complex
7. | License | GNU and GPU | MIT
8. | Connection name | OS Thread | OS Process
9. | Suitable for | Simple applications | Large and complex problems
10. | Troubleshooting | Easier than PostgreSQL | More complex
11. | Overall performance | Good for heavy [operations](https://coderpad.io/blog/development/optimize-mysql-database-schema/) | Better by default, works with huge datasets and complex queries.
12. | Syntax | SELECT * FROM records; | SELECT * FROM records;
13. | NoSQL support | After 8.0 version | Fully supported
14. | Documentation | Support for JSON but not JSON indexes | Supports JSON, XML, and major document formats
15. | OS system compatibility | Almost all major OS | Almost all major OS
16. | Data types | Basic data types, such as INT, VARCHAR, etc. | Better range of data formats
17. | Indexes | Only B-Tree such as PRIMARY KEY UNIQUE KEY, FULLTEXT | Hash Index, B-Tree Index, and Partial Indexes
18. | Replication/DR | Master Standby Replication (MSR) | [MSR](https://docs.mirantis.com/msr/3.0/common/msr-system-reqs.html) and improved [WAL](https://www.interdb.jp/pg/pgsql09.html) processing
19. | DBMS type | Relational DBMS | Object-relational DBMS
20. | Community support | Vast community support | Vast community support

### Which One is Best for You: PostgreSQL or MySQL?

After exploring both DBMSs, we can easily determine which one will better suit your needs. Because PostgreSQL uses more advanced technologies and tools and is more complex, it is the go-to option for complex and highly advanced [data operations](https://coderpad.io/blog/development/window-functions-aggregate-data-postgres/). PostgreSQL handles extraordinary situations more effectively and has fully developed tools, security, and other algorithms. So, when working with cloud technology, machine learning, and artificial intelligence, PostgreSQL is an excellent choice for use in these areas.

On the other hand, regular applications, such as e-commerce websites, desktop applications, logging applications, and data warehousing, have fewer requirements for data consistency. In these areas, MySQL would be a good fit. Because these aren’t complex, the amount of data management is also comparably lower.

## Conclusion

To conclude, here are a few takeaways:

- We introduced MySQL and PostgreSQL and discussed many points of comparison.
- MySQL is a relational DBMS that uses CRUD operations to implement its working to the code.
- PostgreSQL is an object-relational database system that allows object-oriented data structuring by creating customized data types.
- MySQL is an open-source, easy-to-use DBMS, whereas PostgreSQL is a complex yet accessible and open-source DBMS.
- MySQL is suitable for normal development and desktop applications.
- PostgreSQL is meant for advanced data operations because it is more complex and requires users to possess more skills and training.

This post was written by Gourav Bais. [Gourav](https://www.analyticsvidhya.com/blog/author/gourav29/?utm_source=social&utm_medium=linkedin&utm_campaign=author_profile) is an applied machine learning engineer skilled in computer vision/deep learning pipeline development, creating machine learning models, retraining systems, and transforming data science prototypes to production-grade solutions.

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