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  1. Home
  2. /
  3. AWS Glue
Logo of AWS Glue

AWS Glue

byAmazon Web Services (AWS)
in
4.4
Market Presence: Data Integration Tools, Integration Platform as a Service

Overview

Product Information on AWS Glue

Updated 13th October 2025

What is AWS Glue?

AWS Glue is a cloud-based software designed for data integration and ETL (extract, transform, load) tasks. It enables users to prepare and load data for analytics by providing automated data discovery, schema inference, and job scheduling capabilities. The software supports integration with data stored in various sources, including relational databases, data lakes, and data warehouses. AWS Glue aids in cataloging metadata, transforming raw data, and orchestrating workflows through serverless execution, helping organizations streamline and automate the movement and transformation of large datasets for analytics and reporting.

AWS Glue Pricing

AWS Glue software pricing model is based on a pay-as-you-go structure where charges are incurred for use of data processing units per minute, as well as for data catalog storage and requests. There are no upfront commitments, and users are billed monthly according to usage levels across various Glue features including ETL jobs, crawlers, and data catalog operations.

Overall experience with AWS Glue

Data Analyst
3B - 10B USD, Finance (non-banking)
FAVORABLE

“Efficient large-scale data processing, but mastering optimization is challenging”

4.0
May 30, 2026
Overall. My experience with AWS Glue has been very positive. It is a feature-rich, serverless data integration platform that simplifies building and managing ETL pipelines at scale. The platform is particularly strong in metadata management, data transformation and seamless integration with AWS native services. AWS Glue stands out due to its wide range of connectors, automated schema delivery, and flexible transformation capabilities using spark. While it requires some expertise to fully leverage advanced features like optimization and data modelling, it provides a comprehensive and scalable solution for modern data engineering use cases.
Director of IT Services
<50M USD, Construction
CRITICAL

“Integrating serverless data into AWS facilitates synergies but requires extra resources”

3.0
Apr 22, 2026
Based on my personal experience, this serverless data integration tool from Amazon Web Services seems like a good product because it allows you to extract, transform, and load data from different sources, automating data pipelines very effectively. The part that raised the most questions for us is that if you don't optimize your jobs, your costs will increase.
Automated Translation from Spanish

About Company

Company Description

Updated 6th March 2025

Amazon Web Services (AWS), established in 2006, is focused on providing essential infrastructure services to businesses globally in the form of cloud computing. The key advantage offered through cloud computing, particularly via AWS, is its capacity to shift fixed infrastructure expenses into flexible costs. Businesses have been able to forgo extensive planning and procurement of servers and other Information Technology (IT) resources, owing to AWS. AWS seeks to provide businesses with prompt and cost-effective access to resources using Amazon's expertise and economies of scale, as and when their business requires. Currently, AWS offers a robust, scalable, economic infrastructure platform on the cloud powering an extensive array of businesses worldwide. It operates across numerous industries with data center locations in various parts of the globe including U.S., Europe, Singapore, and Japan.

Company Details

Updated 23rd December 2024
Company type
Public
Year Founded
2006
Head office location
Seattle, United States
Number of employees
10001+
Website
http://aws.amazon.com

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Key Insights

A Snapshot of What Matters - Based on Validated User Reviews

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Peer Discussions

AWS Glue Reviews and Ratings

Showing data for 552 ratings and reviews for Data Integration Tools market. View all 581 ratings and reviews across markets for a complete picture.

4.4

(552 Ratings)

Rating Distribution

5 Star
45%
4 Star
44%
3 Star
10%
2 Star
0%
1 Star
0%
Why ratings and reviews count differ?

Customer Experience

Evaluation & Contracting

4.4

Integration & Deployment

4.4

Service & Support

4.4

Product Capabilities

4.4

Filter Reviews
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Last 12 Months
Star Rating
Reviewer Type
Reviewer's Company Size
Reviewer's Industry
Reviewer's Region
Reviewer's Job Function
  • Data Analyst
    1B-10B USD
    Finance (non-banking)
    Review Source

    Efficient large-scale data processing, but mastering optimization is challenging

    4.0
    May 30, 2026
    Overall. My experience with AWS Glue has been very positive. It is a feature-rich, serverless data integration platform that simplifies building and managing ETL pipelines at scale. The platform is particularly strong in metadata management, data transformation and seamless integration with AWS native services. AWS Glue stands out due to its wide range of connectors, automated schema delivery, and flexible transformation capabilities using spark. While it requires some expertise to fully leverage advanced features like optimization and data modelling, it provides a comprehensive and scalable solution for modern data engineering use cases.
  • Audit Manager
    50M-1B USD
    Software
    Review Source

    Powerful for batch ETL at scale, but with a learning curve and costs to consider

    4.0
    May 28, 2026
    AWS Glue has been a fundamental tool for our data integration and transformation pipelines. The ability to run serverless ETL jobs without managing infrastructure significantly reduces operational overhead. Its integration with S3, Redshift, and the Glue Data Catalog makes it a solid choice for data architectures on AWS.
  • Accounts Assistant
    <50M USD
    Insurance (except health)
    Review Source

    AWS Glue Streamlines Data Integration but Faces Debugging and Startup Time Challenges

    4.0
    Jan 8, 2026
    AWS has worked well for buliding scalable data integration pipelines on AWS. My overall experience is positive and it's easy to use. It's a great tool for production-grade data engineering.
  • Senior It Sysadmin
    50M-1B USD
    Travel and Hospitality
    Review Source

    Serverless AWS Glue Enhances Data Cataloging Yet Faces Job Latency And Expense Issues

    4.0
    Apr 9, 2026
    Our experience with AWS Glue has been overall positive, as it fits perfectly into our AWS-native data architecture. Being serverless, it allows our team to focus on data engineering rather than managing Spark clusters.
  • Data Analyst
    Gov't/PS/Ed
    Education
    Review Source

    Scalable ETL Platform Reduces Overhead Yet Faces UI and Startup Time Issues

    5.0
    May 13, 2026
    We have been using AWS Glue for ETL workflows, data movement, and integration between S3, Redshift and other AWS services. Overall, the experience has been positive. The platform is highly scalable, easy to integrate within the AWS ecosystem, and significantly reduces infrastructure management overhead because of its serverless architecture.
...
Showing Result 1-5 of 727

Recommended Gartner Insights

  • Critical Capabilities for Data Integration Tools
  • Magic Quadrant for Data Integration Tools
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User Sentiment About AWS Glue
Reviewer Insights for: AWS Glue
Deciding Factors: AWS Glue Vs. Market Average
Performance of AWS Glue Across Market Features

AWS Glue Likes & Dislikes

Like

1) There is a wide range of data connectors. AWS Glue supports native connectors for AWS services like S3, Redshift, RDS, DynamoDB, and Aurora along with JDBC connectors for external databases and SaaS integrations. This makes it easy to integrate data across hybrid and multi-source environments. 2) The Glue data catalog feature is great as it acts as a centralized metadata repository, enabling schema versioning, table definitions, and integration with services like Athena and Redshift spectrum which is crucial for data governance and discoverability. 3) Glue also has automated crawlers which detect schemas, classify data and update metadata tables which reduces manual effort in onboarding and maintaining datasets 4) Glue Handles large scale aggregation workloads efficiently using distributed processing. It supports grouping by operations, window functions and partition-based aggregation which makes it useful for analytics pipelines.

Like

It integrates seamlessly with the AWS ecosystem, which is a significant advantage for me due to the synergies it offers. It provides savings and efficiency because, being serverless, you don't need to allocate additional servers from your infrastructure. It's effective at handling large amounts of data without presenting any issues, based on our experience.

Automated Translation from Spanish
Like

The combination of the Data Catalog with serverless jobs allows building scalable data pipelines without worrying about the underlying infrastructure. Native integration with other AWS services and support for multiple data formats make it very versatile for different use cases

Dislike

1) Complex debugging and monitoring. Debugging Spark jobs and tracking failures can be difficult due to limited visibility and reliance on logs. 2) requires an understanding of spark, partitioning, and performance tuning to fully utilize transformation and aggregation capabilities. 3) Cost optimization requires attention. Inefficient job design (improper aggregation or large data scans) can lead to higher costs if not managed properly.

Dislike

Getting it up and running is difficult and complex, and you have to allocate more resources than you initially planned. It's completely dependent on AWS since it's part of their ecosystem. Furthermore, complex data analysis or debugging doesn't provide much information, or at least not enough to be agile; you need time to understand how it works and apply your own criteria.

Automated Translation from Spanish
Dislike

Slow cold starts: jobs can take several minutes to initialize, making it unsuitable for low-latency processing needs Complex debugging: identifying errors in Spark scripts within Glue isn't always intuitive, and Cloudwatch logs can be difficult to navigate. Glue Studio limitations: the visual interface is useful for simple cases but falls short for complex transformations or advanced custom logic.