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Python VS AWS Glue

Compare Python VS AWS Glue and see what are their differences

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Python logo Python

Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.

AWS Glue logo AWS Glue

Fully managed extract, transform, and load (ETL) service
  • Python Landing page
    Landing page //
    2021-10-17

  • AWS Glue Landing page
    Landing page //
    2022-01-29

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.

AWS Glue features and specs

  • Fully Managed
    AWS Glue is a fully managed ETL (Extract, Transform, Load) service, which means you don't need to manage any underlying infrastructure. This reduces the operational overhead and allows you to focus on the data processing tasks.
  • Scalability
    AWS Glue can automatically scale resources up or down based on the demand and workload, ensuring optimal performance without manual intervention.
  • Serverless
    Being serverless, there are no servers to manage or maintain. You only pay for the resources that you consume, which can result in significant cost savings.
  • Integrated Data Catalog
    AWS Glue comes with a built-in data catalog that helps you organize and discover your data. It automatically indexes and maintains metadata about your data, making it easier to manage.
  • Support for Multiple Data Sources
    AWS Glue supports a variety of data sources including Amazon S3, RDS, Redshift, and many external databases, providing flexibility in your ETL processes.
  • Developer Tools
    AWS Glue provides developer endpoints for custom ETL logic, and integrates with AWS SDKs, Boto3, and the AWS CLI, allowing for a flexible development experience.

Possible disadvantages of AWS Glue

  • Complex Pricing
    The pricing model for AWS Glue can be complicated, involving multiple components such as Data Processing Units (DPUs), data catalog storage, and crawler costs, which may make it hard to estimate costs.
  • Learning Curve
    There is a significant learning curve for developers who are new to AWS Glue, especially when it comes to understanding its various components and configurations.
  • Performance for Small Datasets
    AWS Glue is optimized for large-scale data processing, which may result in suboptimal performance and higher costs for smaller datasets.
  • Vendor Lock-in
    Using AWS Glue ties you to the AWS ecosystem, making it harder to switch to another cloud provider without significant rework of your ETL pipelines and data catalog.
  • Limited Debugging Tools
    The debugging and troubleshooting tools for AWS Glue are somewhat limited compared to other mature ETL tools, which may complicate the development and maintenance of ETL jobs.
  • Job Run Delays
    There can be delays in job startup times, which can be problematic for certain time-sensitive applications requiring near real-time data processing.

Analysis of AWS Glue

Overall verdict

  • AWS Glue is generally considered a good option for organizations looking for a powerful, scalable, and cost-effective ETL solution within the AWS ecosystem. Its ease of integration with AWS services, managed nature, and capability to handle large volumes of data make it a strong choice, particularly for teams that are already using AWS services.

Why this product is good

  • AWS Glue is a fully managed ETL (Extract, Transform, Load) service that makes it easy to prepare and transform data for analytics, machine learning, and application development. It is particularly beneficial for its serverless architecture, which allows users to run data processing jobs without the need to manage any infrastructure. The service integrates seamlessly with other AWS services like S3, RDS, and Redshift, providing a robust ecosystem for data processing. It also supports a wide range of data sources and formats, and offers a graphical interface for easy job creation and monitoring.

Recommended for

  • Organizations already using AWS services and looking to streamline their ETL processes.
  • Data engineers and developers who need a scalable solution to handle large datasets without managing infrastructure.
  • Companies that require seamless integration with a wide array of data storage options and formats.

Python videos

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

AWS Glue videos

Build ETL Processes for Data Lakes with AWS Glue - AWS Online Tech Talks

More videos:

  • Review - AWS re:Invent BDT 201: AWS Data Pipeline: A guided tour
  • Review - Getting Started with AWS Glue Data Catalog
  • Review - Bajaj Housing Finance Limited: Serverless Data Pipelines with AWS Glue and Amazon Aurora PGSQL

Category Popularity

0-100% (relative to Python and AWS Glue)
Programming Language
100 100%
0% 0
ETL
0 0%
100% 100
OOP
100 100%
0% 0
Data Integration
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 Python and AWS Glue

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

AWS Glue Reviews

Best ETL Tools: A Curated List
AWS Glue is a fully managed serverless ETL service from Amazon Web Services (AWS) designed to automate and simplify the data preparation process for analytics. Its serverless architecture eliminates the need to manage infrastructure. As part of the AWS ecosystem, it is integrated with other AWS services, making it a go-to choice for cloud-based data integration for...
Source: estuary.dev
10 Best ETL Tools (October 2023)
AWS Glue is an end-to-end ETL offering intended to make ETL workloads easier and more integratable with the larger AWS ecosystem. One of the more unique aspects of the tool is that it is serverless, meaning Amazon automatically provisions a server and shuts it down following the completion of the workload.
Source: www.unite.ai
15+ Best Cloud ETL Tools
AWS Glue is a serverless data integration service designed to streamline analytics, machine learning, and app development tasks. It discovers, prepares, and moves data from a myriad of sources and offers a seamless integration experience. AWS Glue's inclusive toolset and automatic scaling let you focus on gaining insights from data instead of managing infrastructure.
Source: estuary.dev
Top 14 ETL Tools for 2023
Notably, AWS Glue is serverless, which means that Amazon automatically provisions a server for users and shuts it down when the workload is complete. AWS Glue also includes features such as job scheduling and โ€œdeveloper endpointsโ€ for testing AWS Glue scripts, improving the toolโ€™s ease of use.
A List of The 16 Best ETL Tools And Why To Choose Them
Better yet, when interacting with AWS Glue, practitioners can choose between a drag-and-down GUI, a Jupyter notebook, or Python/Scala code. AWS Glue also offers support for various data processing and workloads that meet different business needs, including ETL, ELT, batch, and streaming.

Social recommendations and mentions

Based on our record, Python seems to be a lot more popular than AWS Glue. While we know about 299 links to Python, we've tracked only 16 mentions of AWS Glue. 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.

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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AWS Glue mentions (16)

  • Optimizing AWS Costs for AI Development in 2025
    Managed Services: This includes the per-token costs of using services like Amazon Bedrock, the hosting fees for SageMaker endpoints, and the costs associated with data pipelines using services like Glue or Lambda. - Source: dev.to / 11 months ago
  • Introducing RisingWave's Hosted Iceberg Catalog-No External Setup Needed
    However, using any Iceberg engine traditionally requires a first, crucial step: setting up and configuring an Iceberg catalog. This catalog is responsible for managing the table metadata. While flexible, this often means provisioning and managing a separate service like AWS Glue, a dedicated PostgreSQL database for the JDBC catalog, or a REST service. This adds an extra layer of configuration and operational... - Source: dev.to / about 1 year ago
  • Vector: A lightweight tool for collecting EKS application logs with long-term storage capabilities
    In this article, we present an architecture that demonstrates how to collect application logs from Amazon Elastic Kubernetes Service (Amazon EKS) via Vector, store them in Amazon Simple Storage Service (Amazon S3) for long-term retention, and finally query these logs using AWS Glue and Amazon Athena. - Source: dev.to / about 1 year ago
  • Build Your Movie Recommendation System Using Amazon Personalize, MongoDB Atlas, and AWS Glue
    AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy to prepare and load data for analysis. It helps bridge the gap between our MongoDB Atlas data and the services we'll use for recommendation. - Source: dev.to / over 2 years ago
  • Using Snowflake data hosted in GCP with AWS Glue
    AWS Glue is a fully managed extract, transform, and load (ETL) service provided by Amazon Web Services (AWS). It is designed to make it easy for users to prepare and load their data for analysis. AWS Glue simplifies the process of building and managing ETL workflows by providing a serverless environment for running ETL jobs. - Source: dev.to / over 2 years ago
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What are some alternatives?

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

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

Xplenty - Xplenty is the #1 SecurETL - allowing you to build low-code data pipelines on the most secure and flexible data transformation platform. No longer worry about manual data transformations. Start your free 14-day trial now.

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

AWS Database Migration Service - AWS Database Migration Service allows you to migrate to AWS quickly and securely. Learn more about the benefits and the key use cases.

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

Skyvia - No-code data integration with 200+ data sources, including Salesforce, Dynamics 365, HubSpot, Asana, SQL Server, MySQL, Snowflake, BigQuery, CSV, FTP, and more.