Software Alternatives, Accelerators & Startups

Pandas VS Ruby on Rails

Compare Pandas VS Ruby on Rails and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Ruby on Rails logo Ruby on Rails

Ruby on Rails is an open source full-stack web application framework for the Ruby programming...
  • Pandas Landing page
    Landing page //
    2023-05-12
  • Ruby on Rails Landing page
    Landing page //
    2023-10-23

We recommend LibHunt Ruby for discovery and comparisons of trending Ruby projects. Also, to find more open-source ruby alternatives, you can check out libhunt.com/r/rails

Pandas features and specs

  • Data Wrangling
    Pandas offers robust tools for manipulating, cleaning, and transforming data, making it easier to prepare data for analysis.
  • Flexible Data Structures
    Pandas provides two primary data structures: Series and DataFrame, which are flexible and offer powerful capabilities for handling various types of datasets.
  • Integration with Other Libraries
    Pandas integrates seamlessly with other Python libraries such as NumPy, Matplotlib, and SciPy, facilitating comprehensive data analysis workflows.
  • Performance with Data Size
    For data sizes that fit into memory, Pandas performs excellently with operations and computations being highly optimized.
  • Rich Feature Set
    Pandas provides a wide array of functionalities, including but not limited to group-by operations, merging and joining data sets, time-series functionality, and input/output tools.
  • Community and Documentation
    Pandas has a strong community and extensive documentation, offering a wealth of tutorials, examples, and support for new and experienced users alike.

Possible disadvantages of Pandas

  • Memory Consumption
    Pandas can become memory inefficient with very large datasets because it relies heavily on in-memory operations.
  • Single-threaded
    Many Pandas operations are single-threaded, which can lead to performance bottlenecks when handling very large datasets.
  • Steep Learning Curve
    For users who are new to data analysis or Pandas, there can be a steep learning curve due to its extensive capabilities and complex syntax at times.
  • Less Suitable for Real-time Analytics
    Pandas is not designed for real-time analytics and is better suited for batch processing due to its in-memory operations and single-threaded nature.
  • Error Handling
    Error messages in Pandas can sometimes be cryptic and hard to interpret, making debugging a challenge for users.

Ruby on Rails features and specs

  • Rapid Development
    Ruby on Rails uses conventions over configurations which allows developers to build applications quickly. It comes with a wealth of built-in tools and libraries that streamline the development process.
  • Community Support
    Rails has a vibrant and active community. This means a lot of third-party libraries (gems) are available, and you can easily find help and resources.
  • Convention over Configuration
    Rails emphasizes convention over configuration, which reduces the number of decisions developers need to make. This can increase productivity and consistency across projects.
  • Built-in Testing
    Rails comes with a strong built-in testing framework, making it easier to test your application and ensure that it works as expected.
  • Scalability Options
    Although it has a reputation for not being the most scalable framework, Rails can be made scalable with good architecture and the right tools.
  • RESTful Design
    Rails promotes RESTful application design, which means that it aligns well with best practices in web development and makes it easier to build APIs.

Possible disadvantages of Ruby on Rails

  • Performance
    Ruby on Rails can be slower than some other frameworks, particularly for applications that require a lot of computation or have high traffic.
  • Learning Curve
    While Rails makes many things easier with its conventions, this can create a steep learning curve for newcomers who need to understand the 'Rails way' of doing things.
  • Scalability Concerns
    Due to its monolithic nature, scaling Rails can be challenging, requiring significant architectural changes and optimizations.
  • Lesser Flexibility
    The conventions that make Rails easy to use can also be limiting. When you need to do something outside the typical Rails flow, it may be harder to implement.
  • Runtime Speed
    Ruby, the language that Rails is built on, is generally slower in terms of execution speed compared to other languages like Java or C++.
  • Memory Consumption
    Rails applications can consume a lot of memory, which can be a concern for large-scale applications or those with limited resources.

Pandas videos

Ozzy Man Reviews: Pandas

More videos:

  • Review - Ozzy Man Reviews: PANDAS Part 2
  • Review - Trash Pandas Review with Sam Healey

Ruby on Rails videos

Ruby On Rails Biggest Waste Of Time In 2020 | Ruby on Rails Dead

More videos:

  • Tutorial - Ruby on Rails Tutorial | Build a Book Review App - Part 1

Category Popularity

0-100% (relative to Pandas and Ruby on Rails)
Data Science And Machine Learning
Developer Tools
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Web Frameworks
0 0%
100% 100

User comments

Share your experience with using Pandas and Ruby on Rails. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Pandas and Ruby on Rails

Pandas Reviews

25 Python Frameworks to Master
Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.
Source: kinsta.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
Source: www.xplenty.com

Ruby on Rails Reviews

  1. Stan
    · Founder at SaaSHub ·
    The most productive web framework

    Yes, there are other more trending frameworks; however, nothing reaches the productivity of Rails. It's simply unbeatable if you have a small team.

    For example both SaaSHub and LibHunt were built on Rails.

    🏁 Competitors: Django, Laravel

Top 9 best Frameworks for web development
The best frameworks for web development include React, Angular, Vue.js, Django, Spring, Laravel, Ruby on Rails, Flask and Express.js. Each of these frameworks has its own advantages and distinctive features, so it is important to choose the framework that best suits the needs of your project.
Source: www.kiwop.com
Top 5 Laravel Alternatives
In terms of documentation, guidelines, and libraries, Ruby on Rails is the superior framework for smaller applications. Since it entered the online scene before Laravel, its community is larger and more well-liked among programmers. When compared to other Laravel alternatives, Ruby’s code is much simpler to understand and write.
Top 10 Phoenix Framework Alternatives
While modern frameworks try to minimize the tradeoffs to a limited extent, none of them has come closer to the implementation of the Phoenix Framework, which offers Ruby on Rails levels of productivity while being one of the fastest frameworks available in the market.
10 Ruby on Rails Alternatives For Web Development in 2022
Once a prolific web development technology, in 2021, both Ruby and Ruby on Rails are considered dying technologies. The data speaks for itself. In October 2021, Ruby lost 3 ranks in the Tiobe Index compared to October 2020 and became the 16th most searched programming language. The same decline in Ruby on Rails popularity is demonstrated by Google Trends. The language...
Get Over Ruby on Rails — 3 Alternative Web Frameworks Worth Checking Out
Disclaimer: I started working on this article before the big controversy about Basecamp happened. I don’t want to make any point about this in the article. Regardless of what DHH and others are saying on different topics, Ruby on Rails is still a great piece of software and will continue to be. But there are some great alternatives as well that I would like to highlight.

Social recommendations and mentions

Based on our record, Pandas should be more popular than Ruby on Rails. It has been mentiond 219 times since March 2021. 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.

Pandas mentions (219)

  • Top Programming Languages for AI Development in 2025
    Libraries for data science and deep learning that are always changing. - Source: dev.to / 7 days ago
  • How to import sample data into a Python notebook on watsonx.ai and other questions…
    # Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / 23 days ago
  • How I Hacked Uber’s Hidden API to Download 4379 Rides
    As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / 27 days ago
  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • Sample Super Store Analysis Using Python & Pandas
    This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 8 months ago
View more

Ruby on Rails mentions (140)

  • Indie Hacking with Open Source Tools: Innovating on a Budget
    This ecosystem is fueled by repositories hosting powerful languages, functions, and versatile tools—from backend frameworks like Django and Ruby on Rails to containerization with Docker and distributed version control via Git. Moreover, indie hackers can also utilize open source design tools (e.g. GIMP, Inkscape) and analytics platforms such as Matomo. - Source: dev.to / 2 days ago
  • Charybdis ORM: Building High-Performance Distributed Rust Backends with ScyllaDB
    Ruby on Rails (RoR) is one of the most renowned web frameworks. When combined with SQL databases, RoR transforms into a powerhouse for developing back-end (or even full-stack) applications. It resolves numerous issues out of the box, sometimes without developers even realizing it. For example, with the right callbacks, complex business logic for a single API action is automatically wrapped within a transaction,... - Source: dev.to / 12 days ago
  • Ask HN: What's the ideal stack for a solo dev in 2025
    As it's just you I'd stick with Ruby on Rails 8[1] as you already know it and I think it could realistically easily achieve what you're proposing. There's lots of libraries to for calling out external AI services. e.g. Something like FastMCP[2] From the sound of it that's all you need. I'd use Hotwire[3] for the frontend and Hotwire Native if you want to rollout an app version quickly. I'd back it with... - Source: Hacker News / about 1 month ago
  • Open Source: A Goldmine for Indie Hackers – Unleashing Creativity and Collaboration
    One of the standout benefits of open source software is its cost-effectiveness. Indie hackers can leverage robust tools such as MySQL and Python, which eliminate the financial barrier to high-quality software solutions. Frameworks like Django and Ruby on Rails enable swift development cycles, reducing the time-to-market for innovative ideas. This low-cost, high-efficiency approach allows entrepreneurs to focus on... - Source: dev.to / 2 months ago
  • Indie Hacking with Open Source Tools: Innovating on a Budget
    Frameworks such as Django and Ruby on Rails simplify web development, while tools like Docker ensure consistency across environments. - Source: dev.to / 2 months ago
View more

What are some alternatives?

When comparing Pandas and Ruby on Rails, you can also consider the following products

NumPy - NumPy is the fundamental package for scientific computing with Python

Laravel - A PHP Framework For Web Artisans

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Django - The Web framework for perfectionists with deadlines

OpenCV - OpenCV is the world's biggest computer vision library

ASP.NET - ASP.NET is a free web framework for building great Web sites and Web applications using HTML, CSS and JavaScript.