Name: AWS Glue
Rating: 4.3 (534 reviews)

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.

Overall experience with AWS Glue

Accounts Assistant

<50M USD, Insurance (except health)

FAVORABLE

“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.

Operations Associate

50M - 250M USD, IT Services

CRITICAL

“Strong Data Management Features in AWS Glue Balanced By Log and Budget Uncertainty”

3.0

Feb 10, 2026

AWS Glue works well for basic ETL and data integration tasks, but the experience feels average overall.

About Company

Company Description

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

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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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

I like AWS Glue because it is fully serverless. ELT service that eliminates the need to manage infrastructure while automatically scaling with data volume. It integrates seamlessly with AWS services such as S3, Athena, Redshift, and Snap Lake Formation and Glue, simplifies data transformation using Pyspark and spark SQL and its data catalog and crawlers make schema discovery and metadata management easy.

I like the serverless model, which removes the need to manage infrastructure. It scales well for large data jobs. integration with AWS data stack is strong. The data catalog is also useful for managing schemas and metadata.

- Serverless: No infrastructure to manage; the service automatically scales compute resources based on the workload, which reduces operational overhead - Deep AWS Integration: Seamless connectivity withs S3, Athena, Redshift, and Lake Formation creates a unified ecosystem for data discovery and processing - Automated Cataloging: The Glue Crawlers and Data Catalog are excellent for automatically discovering schemas and maintaining consistent metadata across the environment

AWS glue can be difficult to debug due to verbose spark logs and limited error visibility. Job startup times are slow because of cold starts, managing dependencies and spark versions can be complex and cost may inefficient DPU allocations. It is not suited for low-latency or real-time processing use cases.

Job debugging is difficult when failure occurs, logs are not always clear. Costs can rise without clear signals.

- Debugging Difficulties: Troubleshooting failed jobs often frustrating; the logs in CloudWatch can be overwhelming and dont always point clearly to the root cause in the Spark code - Job Startup Latency: The cold start time for Glue jobs ti initialize can be significant, making it less ideal for near-real-time or low-latency ETL equirements - Cost Predictability: Without strict monitoring and fine-tuning of DPUs, costs can scale quickly and unexpectedly; especially for jobs that arent optimized for parallel processing

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Peer Discussions

AWS Glue Reviews and Ratings

Recommended Gartner Insights

<50M USD

Insurance (except health)

Review Source

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

Senior It Sysadmin

50M-1B USD

Travel and Hospitality

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

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

Software

AWS Glue Handles ETL Load Well Yet Lacks Intuitive Visual Error Reporting

Feb 17, 2026

AWS Glue is a great tool that is used a lot in our ETL processes. It functions well under high workloads and seamlessly integrates into the AWS environment, making it a natural choice for any team using AWS and their data architecture on it.

Engineer

Energy and Utilities

AWS Glue Offers Seamless ETL Integration But Faces Cold Start and Debug Challenges

5.0

Mar 3, 2026

We've had a reasonably great experience using AWS Glue for various ETL jobs. Its severless capabilities fall right in line with what our team is comfortable with, and as with most AWS products, the native integrations make connective services a breeze. Cold-start times can be a drag at times and debugging can be a little painful, but you can't ignore the power of this tool.

ANALYTICS & BUSINESS INTELLIGENCE DIRECT

1B-10B USD

Banking

Serverless Data Integration Offers Scalability But Requires Advanced Engineering Skills

Nov 25, 2025

Strong serverless data integration that scales well. Good for ETL, cataloguing and orchestration but requires engineering skills to get the most out of it. Overall a positive experience.