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AWS Glue VS Apache Airflow

Compare AWS Glue VS Apache Airflow and see what are their differences

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AWS Glue logo AWS Glue

Fully managed extract, transform, and load (ETL) service

Apache Airflow logo Apache Airflow

Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
  • AWS Glue Landing page
    Landing page //
    2022-01-29
  • Apache Airflow Landing page
    Landing page //
    2023-06-17

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.

Apache Airflow features and specs

  • Scalability
    Apache Airflow can scale horizontally, allowing it to handle large volumes of tasks and workflows by distributing the workload across multiple worker nodes.
  • Extensibility
    It supports custom plugins and operators, making it highly customizable to fit various use cases. Users can define their own tasks, sensors, and hooks.
  • Visualization
    Airflow provides an intuitive web interface for monitoring and managing workflows. The interface allows users to visualize DAGs, track task statuses, and debug failures.
  • Flexibility
    Workflows are defined using Python code, which offers a high degree of flexibility and programmatic control over the tasks and their dependencies.
  • Integrations
    Airflow has built-in integrations with a wide range of tools and services such as AWS, Google Cloud, and Apache Hadoop, making it easier to connect to external systems.

Possible disadvantages of Apache Airflow

  • Complexity
    Setting up and configuring Apache Airflow can be complex, particularly for new users. It requires careful management of infrastructure components like databases and web servers.
  • Resource Intensive
    Airflow can be resource-heavy in terms of both memory and CPU usage, especially when dealing with a large number of tasks and DAGs.
  • Learning Curve
    The learning curve can be steep for users who are not familiar with Python or the underlying concepts of workflow management.
  • Limited Real-Time Processing
    Airflow is better suited for batch processing and scheduled tasks rather than real-time event-based processing.
  • Dependency Management
    Managing task dependencies in complex DAGs can become cumbersome and may lead to configuration errors if not properly handled.

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.

Analysis of Apache Airflow

Overall verdict

  • Yes, Apache Airflow is a good choice for managing complex workflows and data pipelines, particularly for organizations that require a scalable and reliable orchestration tool.

Why this product is good

  • Apache Airflow is considered good because it provides a robust and flexible platform for authoring, scheduling, and monitoring workflows. It is open-source and has a large community that contributes to its continuous improvement. Airflow's modular architecture allows for easy integration with various data sources and destinations, and its UI is user-friendly, enabling effective pipeline visualization and management. Additionally, it offers extensibility through a wide array of plugins and customization options.

Recommended for

    Apache Airflow is recommended for data engineers, data scientists, and IT professionals who need to automate and manage workflows. It is particularly suited for organizations handling large-scale data processing tasks, requiring integration with various systems, and those looking to deploy machine learning pipelines or ETL processes.

AWS Glue videos

+ Add

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

Apache Airflow videos

+ Add

Airflow Tutorial for Beginners - Full Course in 2 Hours 2022

Category Popularity

0-100% (relative to AWS Glue and Apache Airflow)

AWS Glue

Apache Airflow

ETL
100 100%
ETL
0% 0
Workflow Automation
0 0%
Workflow Automation
100% 100
Data Integration
100 100%
Data Integration
0% 0
Automation
0 0%
Automation
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 AWS Glue and Apache Airflow

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 “developer endpoints” for testing AWS Glue scripts, improving the tool’s ease of use.
Source: www.integrate.io
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.
Source: www.datacamp.com

Apache Airflow Reviews

5 Airflow Alternatives for Data Orchestration
While Apache Airflow continues to be a popular tool for data orchestration, the alternatives presented here offer a range of features and benefits that may better suit certain projects or team preferences. Whether you prioritize simplicity, code-centric design, or the integration of machine learning workflows, there is likely an alternative that meets your needs. By...
Source: www.kdnuggets.com
Top 8 Apache Airflow Alternatives in 2024
Apache Airflow is a workflow streamlining solution aiming at accelerating routine procedures. This article provides a detailed description of Apache Airflow as one of the most popular automation solutions. It also presents and compares alternatives to Airflow, their characteristic features, and recommended application areas. Based on that, each business could decide which...
Source: blog.skyvia.com
10 Best Airflow Alternatives for 2024
In a nutshell, you gained a basic understanding of Apache Airflow and its powerful features. On the other hand, you understood some of the limitations and disadvantages of Apache Airflow. Hence, this article helped you explore the best Apache Airflow Alternatives available in the market. So, you can try hands-on on these Airflow Alternatives and select the best according to...
Source: hevodata.com
A List of The 16 Best ETL Tools And Why To Choose Them
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
Source: www.datacamp.com
15 Best ETL Tools in 2022 (A Complete Updated List)
Apache Airflow programmatically creates, schedules and monitors workflows. It can also modify the scheduler to run the jobs as and when required.
Source: www.softwaretestinghelp.com

Social recommendations and mentions

Based on our record, Apache Airflow should be more popular than AWS Glue. It has been mentiond 79 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.

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 / about 2 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 / 3 months 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 / 5 months 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 1 year 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 1 year ago
View more

Apache Airflow mentions (79)

  • dgsh – Directed Graph Shell
    There is a lot of stuff for Python which follows the "express computation as a dag" approach, especially Apache Airflow https://airflow.apache.org/. - Source: Hacker News / 4 days ago
  • Unable to emit metadata to DataHub GMS with Airflow - a solution
    Doing ingestion or data processing with Airflow, a very popular open-source platform for developing and running workflows, is a fairly common setup. DataHub's automatic lineage extraction works great with Airflow - provided you configure the Airflow connection to DataHub correctly. - Source: dev.to / about 2 months ago
  • Top ETL Tools for MongoDB in 2025: Which One Fits Your Use Case?
    Apache Airflow represents the open-source workflow orchestration approach to MongoDB ETL. By combining Airflow's powerful scheduling and dependency management with a Python library like PyMongo, you can build highly customized ETL workflows that integrate seamlessly with MongoDB. - Source: dev.to / 2 months ago
  • Building Effective AI Agents \ Anthropic
    You appear to be making the mistake of assuming that the only valid definition for the term "workflow" is the definition used by software such as https://airflow.apache.org/ https://www.merriam-webster.com/dictionary/workflow thinks the word dates back to 1921. There no reason Anthropic can't take that word and present their own alternative definition for it in the context of LLM tool usage, which is what they've... - Source: Hacker News / 4 months ago
  • The DOJ Still Wants Google to Sell Off Chrome
    Is this really true? Something that can be supported by clear evidence? I’ve seen this trotted out many times, but it seems like there are interesting Apache projects: https://airflow.apache.org/ https://iceberg.apache.org/ https://kafka.apache.org/ https://superset.apache.org/. - Source: Hacker News / 7 months ago
View more

What are some alternatives?

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

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.

Make.com - Tool for workflow automation (Former Integromat)

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.

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

Skyvia - Free cloud data platform for data integration, backup & management

Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.

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