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AWS Glue Reviews

Vendor: Amazon Web Services (AWS)
3.9 out of 5
Badge Ranked 1
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What is AWS Glue?

AWS Glue is a serverless cloud data integration tool that facilitates the discovery, preparation, movement, and integration of data from multiple sources for machine learning (ML), analytics, and application development. The solution includes additional productivity and data ops tooling for running jobs, implementing business workflows, and authoring.

Get the AWS Glue Buyer's Guide and find out what your peers are saying about AWS Glue, Informatica Intelligent Data Management Cloud (IDMC), Denodo and more!
AWS Glue is the #1 ranked solution in top Cloud Data Integration solutions. PeerSpot users give AWS Glue an average rating of 7.8 out of 10. AWS Glue is most commonly compared to Informatica Intelligent Data Management Cloud (IDMC): AWS Glue vs Informatica Intelligent Data Management Cloud (IDMC). AWS Glue is popular among the large enterprise segment, accounting for 65% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 19% of all views.
Buyer's Guide
AWS Glue
March 2026
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AWS Glue mindshare

As of March 2026, the mindshare of AWS Glue in the Cloud Data Integration category stands at 8.8%, down from 20.1% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
AWS Glue8.8%
AWS Database Migration Service7.4%
Informatica Intelligent Data Management Cloud (IDMC)6.3%
Other77.5%
Cloud Data Integration

PeerResearch reports based on AWS Glue reviews

TypeTitleDate
CategoryCloud Data IntegrationMar 25, 2026Download
ProductReviews, tips, and advice from real usersMar 25, 2026Download
ComparisonAWS Glue vs AWS Database Migration ServiceMar 25, 2026Download
ComparisonAWS Glue vs Informatica Intelligent Data Management Cloud (IDMC)Mar 25, 2026Download
ComparisonAWS Glue vs MuleSoft Anypoint PlatformMar 25, 2026Download
Suggested products
TitleRatingMindshareRecommending
Informatica Intelligent Data Management Cloud (IDMC)4.06.3%92%214 interviewsAdd to research
Denodo4.03.1%95%42 interviewsAdd to research
 
 
Key learnings from peers

Valuable Features

AWS Glue stands out for its data catalog, seamless service integration, flexibility with PySpark, straightforward interface, and cost-effectiveness. It offers valuable features like Glue Studio, efficient ETL job handling, intuitive drag-and-drop functionality, and automatic scaling. Users appreciate its ability to manage large volumes of data without requiring dedicated infrastructure, automatic schema detection, and comprehensive transformation capabilities that support machine learning workflows.
  • "AWS Glue has reduced efforts by 60%, which is the main benefit."
  • "AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models."
  • "If I'm working with big data, common languages like Python work quite nicely, which is advantageous."

Room for Improvement

AWS Glue faces challenges in start-up time, language support, and cloud exclusivity. The interface and user-friendliness are lacking with limited programming language support. Connector availability and transformations need expansion. Performance issues, high costs, and inadequate documentation affect usability. Technical support and training resources could be improved. Limitations in error handling, metadata management, and version control hinder efficient data processing. Enhancements in UI, automation, and multi-cloud support would benefit users seeking better flexibility and integration.
  • "When comparing to tools such as Airflow, Glue workflows are still relatively basic in terms of flexibility and complex branching."
  • "In the building and deployment aspects, there is room for improvement. The current process is a bit complicated and could benefit from being more user-friendly and simpler, which would help speed up the deployment process."
  • "I am quite technical, yet when it comes to data pipelines, I prefer using GUIs over code-based calls. It might be easier with a different skill set."

ROI

Companies are experiencing a positive return from AWS Glue as it's often more affordable than alternatives. They find it delivers time savings and increases efficiency. Some, however, are exploring less costly options like ClickHouse due to budget constraints. AWS Glue is recommended for those with fewer pipelines who wish to avoid the time and cost associated with setting up other tools. It provides the expected return on investment within desired timelines.

Pricing

AWS Glue features a pay-as-you-go pricing model considered higher than some alternatives like Athena or EMR, with costs based on Data Processing Units (DPUs) and runtime. Some organizations find it cost-effective for serverless architecture, while others deem it expensive, especially for extensive usage. Enterprise users appreciate cost predictability, but support costs can add up to $25,000 annually. Pricing also varies depending on project scale and organizational requirements, challenging cost optimization and necessitating careful planning.
  • "I rate the tool an eight on a scale of one to ten, where one is expensive, and ten is expensive."
  • "AWS Glue is a paid service that doesn't come under the free trial of AWS."
  • "If you are using the solution for an enterprise business, it will be expensive."

Popular Use Cases

AWS Glue's primary use case is facilitating ETL processes across various organizations. Companies utilize it for file ingestion, data transformation, migration, and analytics. It efficiently manages data from diverse sources like S3, Redshift, and SQL servers, enabling seamless data flow. Users appreciate its ability to handle unstructured data, automate pipelines, and integrate with services such as Apache Airflow and Lambda, emphasizing its role in data engineering and analytics in cloud environments.

Service and Support

AWS Glue customer service receives positive feedback for being responsive and helpful, although some express concerns about response times and costs. Customers find tech support reliable, often resolving issues quickly. Support quality may vary based on subscription levels, with premium options offering faster response. Many users rely on community support and internal teams for quick solutions. Some appreciate detailed guidance and proactive suggestions from support engineers, rating service highly for aiding with complex issues.

Deployment

AWS Glue's initial setup is generally straightforward, benefiting from extensive documentation and the AWS Management Console's user interface. Companies find setup easy, often taking minutes to a few hours. However, they note a learning curve for complex configurations and transformations. Larger deployments may need multiple team members or specific expertise, and users appreciate the serverless nature for rapid deployment. Experience varies but is rated positively, usually around seven to nine out of ten for ease.

Scalability

AWS Glue demonstrates strong scalability features, allowing users to adjust resources easily via its serverless design. It's commonly rated highly for handling diverse data scales efficiently. Many users appreciate its ability to expand without infrastructure management. Some challenges include hidden costs and room for improvement in flexibility. AWS Glue effectively supports various organizational needs, from managing large datasets to enterprise-level applications, with several users expressing plans to expand its adoption due to impressive scaling capabilities.

Stability

AWS Glue is predominantly stable and reliable. Users report minimal issues, with many highlighting its robust integration capabilities and stability rates around eight to ten out of ten. Some users note occasional performance challenges under heavier workloads, though these seem infrequent. Its stability benefits from its architecture, scalability, and AWS management. Many emphasize its reliability for data integration and various production environments, with rare network-related issues noted.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our AWS Glue Buyer's Guide for additional reliable information.

Review data by company size

By reviewers
Company SizeCount
Small Business11
Midsize Enterprise6
Large Enterprise29
By reviewers
By visitors reading reviews
Company SizeCount
Small Business238
Midsize Enterprise125
Large Enterprise663
By visitors reading reviews

Top industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
10%
Manufacturing Company
8%
Government
5%
Insurance Company
5%
Comms Service Provider
5%
Educational Organization
4%
Healthcare Company
4%
University
3%
Retailer
3%
Real Estate/Law Firm
3%
Performing Arts
2%
Construction Company
2%
Outsourcing Company
2%
Energy/Utilities Company
2%
Wholesaler/Distributor
2%
Non Profit
2%
Consumer Goods Company
2%
Media Company
2%
Legal Firm
2%
Marketing Services Firm
2%
Pharma/Biotech Company
2%
Hospitality Company
1%
Recreational Facilities/Services Company
1%
Transportation Company
1%
Renewables & Environment Company
1%
Logistics Company
1%

Compare AWS Glue with alternative products

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Learn more about AWS Glue

AWS Glue allows users to connect to more than 70 diverse data sources and manage data in a centralized data catalog. The solution facilitates visual creation, running, and monitoring of extract, transform, and load (ETL) pipelines to load data into users' data lakes. This Amazon product seamlessly integrates with other native applications of the brand and allows users to search and query cataloged data using Amazon EMR, Amazon Athena, and Amazon Redshift Spectrum.

The solution also utilizes application programming interface (API) operations to transform users' data, create runtime logs, store job logic, and create notifications for monitoring job runs. The console of AWS Glue connects all of these services into a managed application, facilitating the monitoring and operational processes. The solution also performs provisioning and management of the resources required to run users' workloads in order to minimize manual work time for organizations.

AWS Glue Features

AWS Glue groups its features into four categories - discover, prepare, integrate, and transform. Within those groups are the following features:

  • Automatic schema discovery: AWS Glue crawlers connect to the organization's source or target data source through a prioritized list of classifiers to determine the schema for users' data. This feature creates metadata in companies' AWS Glue Data Catalog.

  • Schemas for data stream management: The AWS Glue Schema Registry enables users to validate and control the evolution of streaming data through registered Apache Avro schemas for no additional charge.

  • Automatic scaling based on workload: This feature dynamically scales resources up and down based on workload. The feature controls job resources, removing them depending on how much the workload can be split up.

  • FindMatches: This feature is for machine learning-based data deduplication and cleansing, and works by finding records that are imperfect matches of each other to remove useless data copies.

  • Edit, debug, and test ETL code: This feature helps users who have chosen to interactively develop their ETL code by providing development endpoints for editing, debugging, and testing the code it generates for them.

  • AWS Glue DataBrew: An interactive, point-and-click visual interface for specialists to clean and normalize data without the need to write any code.

  • AWS Glue Interactive Sessions: This feature simplifies the development of data integration jobs by enabling data engineers to interactively prepare and explore data.

  • AWS Glue Studio Job Notebooks: This AWS Glue feature provides serverless notebooks with minimal setup, allowing developers to start working in a timely manner.

  • Complex ETL pipeline building: This feature allows the product to be invoked on a schedule, on demand, or based on an event, allowing users to start multiple jobs in parallel or specify dependencies to build complex ETL pipelines.

  • AWS Glue Studio: This AWS Glue feature allows users to visually transform data through a drag-and-drop interface. The product automatically generates the code for ETL processes for users' data.

AWS Glue Benefits

AWS Glue offers a wide range of benefits for its users. These benefits include:

  • Users of other AWS products can easily onboard with AWS Glue, as it is integrated across a wide range of the company's services.

  • The solution is serverless, which allows for a lower total cost of ownership.

  • AWS Glue offers more power for users, as it automates much of the effort in building, maintaining, and running ETL jobs.

  • The product allows customers to easily discover and search across all their AWS datasets through AWS Glue Data Catalog.

  • AWS Glue does not require additional payment for managing and enforcing schemas for data streams.

  • The solution facilitates the authority of scalable ETL jobs for beginners and non-coding experts through a drag-and-drop interface.

Reviews from Real Users

Mustapha A., a cloud data engineer at Jems Groupe, likes AWS Glue because it is a product that is great for serverless data transformations.

Liana I., CEO at Quark Technologies SRL, describes AWS Glue as a highly scalable, reliable, and beneficial pay-as-you-go pricing model.

AWS Glue customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday

Related questions

  • 65
Which is the best choice for cloud integration: AWS Glue or Informatica Intelligent Cloud Services (IICS)?
  • 23
Is AWS Glue a difficult solution to use if you are a complete beginner?
  • 24
Is AWS Glue effective for AWS-related products only?
  • 33
Why would you choose AWS Glue over other tools?
  • 25
What are the most common use cases for AWS Glue?
  • 41
How does Talend Open Studio compare with AWS Glue?
  • 11
Does AWS Glue offer more flexibility than other ETL (Extract, Transform, Load) tools in terms of data loading?
  • 48
Oracle ICS vs ODI
  • 57
When evaluating Cloud Data Integration, what aspect do you think is the most important to look for?
  • 44
What is data lake storage?

Product Categories

Product Categories
Cloud Data Integration

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AWS Glue Reviews Summary
Author infoRatingReview Summary
application security engineer at Hyperspace IT India4.0No summary available
Python AWS & AI Expert at a tech consulting company4.0I use AWS Glue primarily for serverless integration across various services. Its valuable features include robust transformation capabilities and seamless data preparation, though the deployment process could be simplified. It's integrated with AWS for comprehensive data workflow management.
Principal Consultant at a retailer with 1,001-5,000 employees4.0I use AWS Glue for ETL processes, including data transformation and cleansing for our data warehouse. Its serverless nature and excellent performance are beneficial, though the UI and version upgrades need improvement. Despite some challenges, Glue remains my preferred solution.
Data Architect at a financial services firm with 10,001+ employees2.5I use AWS Glue primarily for data ingestion, curation, and transformation, benefiting from its compatibility with Python for big data. Though clunky and code-heavy, it suits limited pipelines well, especially with AWS, despite preferring GUI-based tools.
AVP at a manufacturing company with 10,001+ employees3.0I use AWS Glue in my company for building data lakes and processing data from various sources like Oracle and MongoDB. It's valuable for managing large data volumes serverlessly, but its high cost, especially if systems are poorly designed, poses significant challenges.
Data Engineer at a tech services company with 501-1,000 employees3.5I use AWS Glue for data processing and find it easy to integrate with other AWS products. However, error handling is challenging, and I find Databricks to be more user-friendly and generally a better solution.
Senior Developer for cloud services at Coforge Growth Agency4.5I primarily use AWS Glue for data ingestion and extraction from multiple sources. The Glue Crawler efficiently updates schemas for large datasets, and the orchestration of ETL pipelines is effective. Improvements are needed in Lambda functions' resource allocation and timeout management.
Offshore Delivery | AWS architect | Manager - Projects at Cognizant4.0I use AWS Glue for efficient data transformation and integration with Apache Airflow, enabling smooth orchestration without cold starts like AWS Lambda. Although managing environment variables could improve, Glue's extended session capability suits our needs better than other solutions.