Software Alternatives, Accelerators & Startups

Cal.com VS Pandas

Compare Cal.com VS Pandas and see what are their differences

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Cal.com logo Cal.com

Cal.com (formerly Calendso) is the open source Calendly alternative.

Pandas logo Pandas

Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
  • Cal.com Landing page
    Landing page //
    2023-10-08
  • Pandas Landing page
    Landing page //
    2023-05-12

Cal.com features and specs

  • Customizable
    Cal.com allows extensive customization to fit various branding and scheduling needs, which makes it adaptable for different types of users including businesses and individuals.
  • Open-source
    Being an open-source platform, Cal.com provides the flexibility for developers to modify and extend the software as per their specific needs, fostering a collaborative development environment.
  • Integrations
    Cal.com offers a wide range of integrations with other software tools like Google Calendar, Microsoft Outlook, and Zoom, enhancing its functionality and making it easier to fit into existing workflows.
  • User-friendly Interface
    Cal.com has an intuitive and clean interface that makes it easy for users of all technical skill levels to set up and manage their scheduling.
  • Privacy-focused
    Cal.com emphasizes data privacy, ensuring user information is handled securely, which is crucial for users who need to comply with regulations like GDPR.

Possible disadvantages of Cal.com

  • Learning Curve
    Although it is highly customizable, the plethora of options and features may result in a steeper learning curve for new users who are not familiar with such scheduling tools.
  • Limited Free Version
    The free version of Cal.com comes with limitations that may not be sufficient for growing businesses or advanced users who require more comprehensive features.
  • Dependency on Integrations
    Cal.com's effectiveness heavily depends on its integrations. Without these integrations, some users might find the tool less useful or incomplete, especially if their primary tools are not supported.
  • Support
    While open-source has many benefits, it may also mean that immediate, personalized support could be limited compared to fully commercial solutions. This might pose a challenge for users needing quick resolutions.
  • Performance
    As an open-source platform, the performance might vary depending on how it is hosted and managed. Suboptimal configurations could lead to slower performance or downtimes.

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.

Cal.com videos

What can you do with Cal? | Cal.com Version 1.1 Launch | 10 new languages

More videos:

  • Review - Cal.com Version 1.0 Launch Event

Pandas videos

Ozzy Man Reviews: Pandas

More videos:

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

Category Popularity

0-100% (relative to Cal.com and Pandas)
Productivity
100 100%
0% 0
Data Science And Machine Learning
Appointments and Scheduling
Data Science Tools
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 Cal.com and Pandas

Cal.com Reviews

I've poked around a while ago at some Calendly alternatives (specifically was lo... | Hacker News
I tried using https://cal.com for a bit but ended up just switching over to https://zcal.co and it has been great so far. All these other scheduling tools end up trying to do too much and always seem to end up a bit clunky and charge absurd amounts for it

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

Social recommendations and mentions

Based on our record, Pandas should be more popular than Cal.com. 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.

Cal.com mentions (56)

  • 5 Side Project Ideas for Developers to Monetize as Micro-SaaS in 2025
    Take Cal.com (https://cal.com/), formerly known as Calendso. It started as an open source alternative to Calendly which offers a free, self-hostable version for users. - Source: dev.to / 3 months ago
  • Using Clerk SSO to access Google Calendar and other service data
    BookMate is an open-source, publicly accessible, lightweight clone of popular booking services like cal.com or Calendly. - Source: dev.to / 5 months ago
  • My Journey into Open Source: First Contributions and Lessons Learned
    Then, I came across Cal.com, a fantastic open-source project for scheduling meetings and managing tasks (super useful for productivity!). I knew the basics of Git but wasn’t quite there with forking, merging branches, and all the intricate Git processes. After some YouTube tutorials, I started to get the hang of things. 😅. - Source: dev.to / 7 months ago
  • Start your own (side) business with open-source in mind
    Cal.com is an open-source event-juggling scheduler for everyone, and is free for individuals. - Source: dev.to / about 1 year ago
  • Fellow HSP entrepreneurs, how do you manage your energy and stress?
    I force clients who want to talk to me to book a call. I use cal.com (free) and my Google Calendar (which its linked to) only allows calls on specific days/times. I have a few "Call Blocks" where they can book. That let's me do calls in a small section of my week, with ample downtime to recover the rest of the week. I'm still learning how many calls a day I can handle. Currently anything more than 2 is too much. Source: over 1 year ago
View more

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 / 25 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 / about 1 month 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 / about 2 months 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 / 4 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 / 9 months ago
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What are some alternatives?

When comparing Cal.com and Pandas, you can also consider the following products

Calendly - Say goodbye to phone and email tag for finding the perfect meeting time with Calendly. It's 100% free, super easy to use and you'll love our customer service.

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

TidyCal - Optimize your schedule with custom booking pages and calendar integrations

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

SavvyCal - A scheduling tool both the sender and the recipient will love.

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