Postgres vs MySQL: Which Is Better For Analytics?

MySQL Vs PostgreSQL

What is PostgreSQL?

PostgreSQL, or Postgres, is a relational database management system (RDBMS) commonly used to store and retrieve tabular data organized in databases and tables. The RDBMS is one of the most widely used in industry due to its extensible framework and reliability. Postgres is an open-source tool that is free to download and use. Postgres is compatible with all major operating systems and supports a number of extensions and plugins. In addition to being a tool to store data, Postgres offers a flavor of SQL to interact with and manage the data it persists.

What is MySQL?

Like Postgres, MySQL is an RDBMS that leverages databases and tables to organize, store, and retrieve tabular data. MySQL is also open source, although heavily supported by Oracle. While MySQL boasts broad functionality, it offers fewer features than Postgres, helping to make it a more “lightweight” tool. MySQL is most commonly used when building web applications, and like Postgres, it implements its own twist on SQL to manage and query data.

Looking into differences (and some similarities) between PostgreSQL and MySQL to help you decide which one suits your needs best.

There are three main similarities between PostgreSQL and MySQL. They are highly popular, they’re open-source, and they both use their own dialects to communicate with the databases.

But how do you decide which one you should use? Nobody has ever decided between two choices based on their similarities. The differences are what make, well, the difference. As a data scientist, you’re probably not that concerned about database architecture, performance, integrity, and all other stuff RDBMS is for.

What will make you give a pass (or not) to a certain database are the possibilities of the SQL dialect and how well it serves you to do your job.

So, while working in analytics, choosing the right database can make a big difference in performance, flexibility, and ease of use. PostgreSQL and MySQL are both very popular open-source databases. But each of them brings its own strengths to the table.

While both Postgres and MySQL share many similarities, plenty of differences help to set these two offerings apart. Below, we’ll break down differences in performance and scalability & features and extensibility. 

Performance and Scalability

Postgres implements multi-version concurrency control, which leverages parallel query strategies without using read or write locks.

Postgres uses strong indexing techniques and data partitioning to help improve query performance and time-to-insights as the amount of data to be stored in a database grows. This allows for Postgres to scale as the amount of data it stores grows.

Postgres generally tends to use more resources (CPU and RAM) than MySQL when running comparable workloads. Postgres’ rich set of features implements more complex query execution techniques, resulting in high resource consumption compared to MySQL. If you use either tool via a managed service provider (such as AWS or Azure), it’s easy to estimate the costs of the workload that you’ll be running.

Features and Extensibility

So far, we’ve referred to both Postgres and MySQL as relational database management systems. Technically, that’s not right.

Postgres is, by definition, an object-relational database management system, or ORDBMS.

Object-relational database management systems implement much of the functionality native to traditional, relational database management systems but combine with support for object-oriented constructs. This includes inheritance, abstraction, or encapsulation.

In addition to the traditional data types that an RDBMS would support, Postgres can store and retrieve data in JSON and XML formats. This functionality enables a wider range of data to be stored, which can be quite useful in a number of applications. As an RDMS, MySQL supports more traditional data types and does not implement the same object-oriented functionality as Postgres.

Postgres is also quite extensible. One of the most notable extensions is PostGIS, which stores and retrieves geospatial data. hstore is another popular tool that’s been developed by the Postgres’ vibrant open-source community. Using a single value, hstore allows for sets of key-value pairs to be stored with Postgres. Although natively feature-rich, MySQL boasts fewer modules and plugins while ensuring core platform consistency and reliability.

Looking Into What They Have In Common

• Both PostgreSQL and MySQL are very widely used & open source. They are among the top RDBMS used worldwide, which is available freely and supported by large communities.

• Each has its own SQL flavor, but the core of querying, joining, filtering remains the same.

  
  

When To Opt On MySQL

• MySQL does an excellent job in scenarios where data is primarily being read, which is very fast.

• It is very easy to start with. If you're running only some simple queries or just want to get things running quick, MySQL’s is very easy to use and it’s performance can be a great advantage.

  
  

When To Opt On PostgreSQL

• PostgreSQL works excellently when handling lot of data and complex queries. It is built for Complexity.

• PostgreSQL supports more advanced SQL features like window functions, CTEs, and JSON support.

• In PostgreSQL you can customize data types, use advanced indexing, and design data models like a pro.

  
  

Insights From Users:

Developers and data experts often agree on with similar observations:

• PostgreSQL has a better quality of life for a modern SQL developer… closer to typical… easier to adapt across platforms.

• PostgreSQL is much more capable… better ANSI/ISO SQL support… better query optimizer.

  For data science roles:

• Go with PostgreSQL as it supports advanced SQL features like window functions, CTEs, and JSON handling.

Summary On Which One Fit By Use Case:

Conclusion

Both MySQL and PostgreSQL are solid choices, but the right one depends on what analytics you need:

• Pick MySQL if you want fast and simplicity matter most, and your tasks are mostly read-only.

• Pick PostgreSQL if you want advanced SQL features, to handle complex queries, and want something that can be flexible with your data.

This post reminds us that while both SQL and PostgreSQL databases have similar features, the best choice depends on current needs and what you will need in the future.