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PostgreSQL VS Python

Compare PostgreSQL VS Python and see what are their differences

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PostgreSQL logo PostgreSQL

PostgreSQL is a powerful, open source object-relational database system.

Python logo Python

Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
  • PostgreSQL Landing page
    Landing page //
    2023-10-21
  • Python Landing page
    Landing page //
    2021-10-17

PostgreSQL features and specs

  • Open Source
    PostgreSQL is an open-source database management system, which means it is free to use, modify, and distribute. This reduces the cost of database management for individuals and organizations.
  • ACID Compliance
    PostgreSQL is fully ACID (Atomicity, Consistency, Isolation, Durability) compliant, ensuring reliable transactions and data integrity.
  • Extensible
    PostgreSQL is highly extensible, allowing users to add custom functions, data types, and operators. This enables tailored solutions to specific requirements.
  • Advanced SQL Features
    PostgreSQL supports advanced SQL features like full-text search, JSON and XML data types, and complex queries, providing powerful tools for database operations.
  • Community Support
    There is a strong and active community around PostgreSQL, offering extensive documentation, forums, and collaborative support, which aids troubleshooting and development.
  • Multiple Indexing Techniques
    PostgreSQL offers a variety of indexing techniques such as B-tree, GIN, GiST, and BRIN, allowing for optimized query performance on various data types.
  • Cross-Platform Availability
    PostgreSQL runs on all major operating systems (Windows, MacOS, Linux, Unix), giving flexibility in deployment and development environments.

Possible disadvantages of PostgreSQL

  • Complex Configuration
    Setting up and configuring PostgreSQL can be complex and time-consuming, especially for beginners, requiring a good understanding of its parameters and best practices.
  • Heavy Resource Consumption
    PostgreSQL can be resource-intensive, consuming significant CPU and memory compared to other database systems, which may affect performance on lower-end hardware.
  • Backup and Restore Process
    The backup and restore process in PostgreSQL is not as straightforward as in some other database systems, requiring more manual intervention and understanding of tools like pg_dump and pg_restore.
  • Replication Complexity
    While PostgreSQL supports replication, setting it up can be more complex than some other databases. Advanced configurations like multi-master replication can be particularly challenging.
  • Steeper Learning Curve
    Due to its advanced features and extensive capabilities, PostgreSQL can have a steeper learning curve, making it harder for new users to get started compared to simpler database systems.
  • Less Third-Party Tool Support
    PostgreSQL has less support from third-party tools compared to more widely adopted databases like MySQL, which can limit options for auxiliary functions like administration, monitoring, and development.

Python features and specs

  • Easy to Learn
    Python syntax is clear and readable, which makes it an excellent choice for beginners and allows for quick learning and prototyping.
  • Versatile
    Python can be used for web development, data analytics, artificial intelligence, machine learning, automation, and more, making it a highly versatile programming language.
  • Large Standard Library
    Python comes with a comprehensive standard library that includes modules and packages for various tasks, reducing the need to write code from scratch.
  • Strong Community Support
    Python has a large and active community, which means a wealth of third-party packages, tutorials, and documentation is available for assistance.
  • Cross-Platform Compatibility
    Python is compatible with major operating systems like Windows, macOS, and Linux, allowing for easy development and deployment across different platforms.
  • Good for Rapid Development
    The high-level nature of Python allows for quick development cycles and fast iteration, which is ideal for startups and prototyping.

Possible disadvantages of Python

  • Performance Limitations
    Python is generally slower than compiled languages like C or Java because it is an interpreted language, which can be a drawback for performance-critical applications.
  • Global Interpreter Lock (GIL)
    The GIL in CPython, the most used Python interpreter, prevents multiple native threads from executing Python bytecodes at once, limiting multi-threading capabilities.
  • Memory Consumption
    Python can be more memory-intensive compared to some other languages, which might be a concern for applications with tight memory constraints.
  • Mobile Development
    Python is not a primary choice for mobile app development, where languages like Java, Swift, or Kotlin are more commonly used.
  • Runtime Errors
    Being a dynamically typed language, Python code can sometimes lead to runtime errors that would be caught at compile-time in statically typed languages.
  • Dependency Management
    Managing dependencies in Python projects can sometimes be complex and cumbersome, especially when dealing with conflicting versions of libraries.

Analysis of PostgreSQL

Overall verdict

  • Yes, PostgreSQL is considered a high-quality and reliable database management system, suitable for a wide range of applications, from small-scale personal projects to large enterprise systems.

Why this product is good

  • PostgreSQL is known for its strong support of SQL standards and excellent documentation, making it reliable for complex database requirements.
  • It provides advanced features such as multi-version concurrency control (MVCC), point-in-time recovery, and support for advanced indexing techniques.
  • PostgreSQL offers robust performance optimization options, powerful extensions, and a highly customizable platform.
  • It has a strong open-source community, ensuring ongoing improvements and support.
  • PostgreSQL is compatible with popular development frameworks and languages, enhancing its versatility.

Recommended for

  • Organizations seeking a scalable and stable database solution with strong compliance with SQL standards.
  • Developers who need advanced features like custom data types and indexing capabilities.
  • Projects requiring robust transactional integrity and data consistency.
  • Businesses looking for a cost-effective open-source database solution with active community support.

PostgreSQL videos

Comparison of PostgreSQL and MongoDB

More videos:

  • Review - PostgreSQL Review
  • Review - MySQL vs PostgreSQL - Why you shouldn't use MySQL

Python videos

Creator of Python Programming Language, Guido van Rossum | Oxford Union

Category Popularity

0-100% (relative to PostgreSQL and Python)
Databases
100 100%
0% 0
Programming Language
0 0%
100% 100
Relational Databases
100 100%
0% 0
OOP
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare PostgreSQL and Python

PostgreSQL Reviews

Database Management Systems (DBMS) Comparison: SQL Server, MySQL, PostgreSQL, MongoDB, Oracle
Choosing the right database management system (DBMS) is a crucial decision that directly impacts your projectโ€™s performance and scalability. With a variety of options โ€” SQL Server, MySQL, PostgreSQL, MongoDB, Oracle, and more โ€” each offering unique features and capabilities, itโ€™s important to carefully match the type of database software to your specific needs. Consider...
Source: blog.devart.com
20 Best Database Management Software and Tools of 2026
Yes, several tools, such as MySQL, PostgreSQL, and MongoDB, offer free versions. While these are robust, enterprise editions or add-ons may come with additional costs for advanced features and support.
Source: infomineo.com
Data Warehouse Tools
Peliqan acts as a bridge, allowing you to e.g. effortlessly pull your PostgreSQL data into Google Sheets for easy access and analysis using its one-click connector. Additionally, Peliqanโ€™s platform provides a user-friendly environment for data exploration, transformation with Magical SQL, and visualization capabilities, all without needing to switch between multiple tools.
Source: peliqan.io
Top 5 BigQuery Alternatives: A Challenge of Complexity
For over three decades, the open-source object-relational database system PostgreSQL has maintained its reputation as a top SQL server due to its features, performance, and reliability. (Heck, Redshift is even based on Postgres!) It's the go-to database solution for large corporations and organizations across a variety of industries from ecommerce to gaming to...
Source: blog.panoply.io
10 Best Database Management Software Of 2022 [+ Examples]
Applications Manager offers out-of-the-box health and performance monitoring for 20 popular databases including RDBMS, NoSQL, in-memory, distributed, and big data stores. It supports both commercial databases such as Oracle, Microsoft SQL, IBM DB2, and MongoDB as well as open source ones like MySQL and PostgreSQL.
Source: theqalead.com

Python Reviews

Pine Script Alternatives: A Comprehensive Guide to Trading Indicator Languages
Technical analysis in trading has come a long way, with various programming languages emerging to support traders in developing custom indicators. While Pine Script has been a popular choice for many, alternatives like Indie, ThinkScript, NinjaScript, MetaQuotes Language (MQL), and even general-purpose languages like Python and C++ are gaining traction. Letโ€™s explore these...
Source: medium.com
Top 5 Most Liked and Hated Programming Languages of 2022
No wonder Python is one of the easiest programming languages to work upon. This general-purpose programming language finds immense usage in the field of web development, machine learning applications, as well as cutting-edge technology in the software industry. The fact that Python is used by major tech giants such as Amazon, Facebook, Google, etc. is good enough proof as to...
Top 10 Rust Alternatives
This programming langue is typed statically and operates on a complied system. It works based on several computing languages Python, Ada, and Modula.
15 data science tools to consider using in 2021
Python is the most widely used programming language for data science and machine learning and one of the most popular languages overall. The Python open source project's website describes it as "an interpreted, object-oriented, high-level programming language with dynamic semantics," as well as built-in data structures and dynamic typing and binding capabilities. The site...
The 10 Best Programming Languages to Learn Today
Python's variety of applications make it a powerful and versatile language for different use cases. Python-based web development frameworks like Django and Flask are gaining popularity fast. It's also equipped with quality machine learning and data analysis tools like Scikit-learn and Pandas.
Source: ict.gov.ge

Social recommendations and mentions

Based on our record, Python seems to be a lot more popular than PostgreSQL. While we know about 299 links to Python, we've tracked only 19 mentions of PostgreSQL. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

PostgreSQL mentions (19)

  • Create an API - Project Setup
    In this new series we will be creating an API written in go, using a framework like Chi, connecting to a PostgreSQL, and have it deployed to a site like Railway. - Source: dev.to / 3 months ago
  • PostgreSQL vs MySQL 2026: Which Database Wins for Modern Apps?
    PostgreSQL 17 Performance Guide โ€” Official docs for the latest performance improvements. - Source: dev.to / 4 months ago
  • #5 - 'The Power of [Separation] Compels You!'
    You also might be saying, Why not include the credit and attribution data with the product data and just use one data file? Thats a great question. I could have for the purpose of this demo, but if there were a backend to this project and a relational database like PostgreSQL attached to it, I would still have both sets of data in separate tables in the database. By using a foreign key between related records in... - Source: dev.to / 10 months ago
  • Convert insert mutation to upsert
    In this quick post, weโ€™ll walk through implementing an Upsert operation in Hasura using PostgreSQL and GraphQL. - Source: dev.to / almost 2 years ago
  • Perfect Elixir: Environment Setup
    Iโ€™m on MacOS and erlang.org, elixir-lang.org, and postgresql.org all suggest installation via Homebrew, which is a very popular package manager for MacOS. - Source: dev.to / over 2 years ago
View more

Python mentions (299)

  • How to Build a Dependency Map of a Legacy Codebase Using AI Tools
    137Foundry provides legacy modernization services that include dependency mapping as a foundational assessment phase. Prettier and ESLint are useful companion tools for enforcing code style consistency as the refactoring proceeds. Node.js and Python.org official documentation are authoritative references for understanding the import and module systems of those runtimes. - Source: dev.to / 2 months ago
  • How to Prepare a Legacy Codebase for AI-Assisted Refactoring
    For Python codebases, tools like Python's built-in ast module and import analysis scripts can generate call graphs. For JavaScript, ESLint and module analysis tools serve a similar purpose. GitHub advanced search can help you find all internal references to a specific function across a large repository. - Source: dev.to / 2 months ago
  • Async Web Scraping in Python: asyncio + aiohttp + httpx (Complete 2026 Guide)
    Import asyncio Import aiohttp From bs4 import BeautifulSoup Async def scrape_and_parse(url: str, session: aiohttp.ClientSession) -> dict: async with session.get(url) as response: html = await response.text() # BeautifulSoup parsing happens after the await โ€” no issue soup = BeautifulSoup(html, "html.parser") return { "url": url, "title": soup.title.string if soup.title... - Source: dev.to / 3 months ago
  • Don't Be Afraid of Git: A Beginner's Guide to Saving and Sharing
    **_Beginner mistake to avoid_** - Writing SQL only inside DBeaver - Always save SQL files in VS Code and commit them **Using PostgreSQL with Python** _**What Python does here**_ Python talks to PostgreSQL and says: - โ€œSave this dataโ€ - โ€œGet this dataโ€ - PostgreSQL listens. Python works. _**Step 1: Install Python **_ - Download from https://python.org - During install, check Add Python to PATH Screenshot... - Source: dev.to / 6 months ago
  • Asyncio: Interview Questions and Practice Problems
    Import time Import requests Import asyncio Import aiohttp Urls = [ 'https://example.com', 'https://httpbin.org/get', 'https://python.org' ] # Synchronous version Def sync_fetch(): for url in urls: response = requests.get(url) print(f"{url} fetched with {len(response.text)} characters") # Async version Async def async_fetch(): async with aiohttp.ClientSession() as session: ... - Source: dev.to / 9 months ago
View more

What are some alternatives?

When comparing PostgreSQL and Python, you can also consider the following products

MySQL - The world's most popular open source database

JavaScript - Lightweight, interpreted, object-oriented language with first-class functions

Microsoft SQL - Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.

Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible

SQLite - SQLite Home Page

C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation