Software Alternatives, Accelerators & Startups

Atlan VS Python

Compare Atlan VS Python and see what are their differences

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Atlan logo Atlan

Atlan is an advanced data workspace developed to offer benefits to many different sources of data.

Python logo Python

Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
  • Atlan Landing page
    Landing page //
    2023-08-23
  • Python Landing page
    Landing page //
    2021-10-17

Atlan

Website
atlan.com
$ Details
-
Release Date
2018 January
Startup details
Country
Singapore
City
Singapore
Founder(s)
Prukalpa Sankar
Employees
50 - 99

Atlan features and specs

  • Collaboration
    Atlan provides a collaborative platform for data teams, allowing users to manage and share data assets, which can enhance teamwork and productivity.
  • Integration
    The tool integrates with a variety of data sources and services, enabling users to easily connect and manage diverse data assets in one place.
  • User-Friendly Interface
    Atlan features an intuitive and user-friendly interface, making it accessible to users of varying technical skills, from data engineers to business analysts.
  • Data Governance
    Atlan offers robust data governance features, such as lineage and metadata management, which help organizations maintain data quality and compliance.
  • Automation
    The platform allows for automation of repetitive tasks, which can save time and reduce errors in data management processes.

Possible disadvantages of Atlan

  • Complexity for Small Teams
    While feature-rich, Atlan might be too complex for smaller teams or projects that do not require comprehensive data management capabilities.
  • Cost
    Atlan's pricing may be a concern for smaller organizations or startups, as advanced features can come at a significant cost.
  • Customization Limitations
    Some users might find the customization options limited compared to other data management platforms, which could impact specific use-case implementations.
  • Learning Curve
    New users may experience a steep learning curve when starting with Atlan due to the extensive range of features and capabilities it offers.

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.

Atlan videos

3-Minute Atlan Demo

More videos:

  • Review - ATLAN SAFE OUTDOORS Tent Chair Blind Review Vs. AMERISTEP Tent Chair Blind (WHATS BETTER??)
  • Review - Atlan: Leveraging Founder-market Fit to Build a Global SaaS Brand

Python videos

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

Category Popularity

0-100% (relative to Atlan and Python)
Business & Commerce
100 100%
0% 0
Programming Language
0 0%
100% 100
Office & Productivity
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 Atlan and Python

Atlan Reviews

We have no reviews of Atlan yet.
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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 Atlan. While we know about 299 links to Python, we've tracked only 2 mentions of Atlan. 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.

Atlan mentions (2)

  • Thoughts around decube.io (data observability and catalog platform)
    After evaluating few solutions in the market: We were in the market to hunt for a solution which will cost under 10k (yearly) considering the cost of opensource will be similar considering DE resource and maintenance cost etc 1. MonteCarlo - Super duper expensive - Unable to hosting in Google Cloud 2. BigEye - Good features 3. Metaplane - Overall good package but when compared to catalog and other features it... Source: over 3 years ago
  • Data lake observability
    I've previously built data lakes on AWS with Glue and you get the data catalog for free but it isn't convenient to explore. Enterprise-grade data catalogs such as Alation are full featured and really decent but come at a higher cost. If your preference is open source, check out Atlan and Amundsen. Source: over 3 years ago

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
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What are some alternatives?

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

Minitab Connect - Minitab Connect is a data management platform that comes with cloud-based data and integration workflows having data governance and integration tools.

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

Microsoft Azure Purview - Microsoft Azure Purview is a unified data governance solution that provides capabilities that cover the entire lifecycle from ingestion to cleansing, transformation, and security.

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

Kylo - Kylo is an end-to-end data lake management software that provides data from many sources in an automated fashion and optimizes it.

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