AWS Glue vs Qlik Compose comparison

Amazon Web Services (AWS) and Qlik are both solutions in the Cloud Data Integration category. Additionally, 90% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 81% of Qlik users who would recommend it.

AWS Glue

Read 50 AWS Glue reviews

9,204 Views
6,903 Comparison Views

90% willing to recommend

Qlik Compose

Read 12 Qlik Compose reviews

2,621 Views
2,123 Comparison Views

81% willing to recommend

AWS Glue

Qlik Compose

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Executive Summary

We performed a comparison between AWS Glue and Qlik Compose based on real PeerSpot user reviews.

Find out what your peers are saying about Amazon Web Services (AWS), Informatica, Palantir and others in Cloud Data Integration.

To learn more, read our detailed Cloud Data Integration Report (Updated: July 2026).

Buyer's Guide

Cloud Data Integration

July 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

AWS Glue

Average Rating

7.8

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Integration (1st)

Qlik Compose

Average Rating

7.6

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Integration (52nd)

Featured Reviews

Sridivya Chillappa

application security engineer at Hyperspace IT India

Efficient data integration reduces operational time and enhances metadata management

For the initial setup with AWS Glue, I find it easy to set up the data catalog and create Glue jobs using the visual editor or the visual code. Setting permission sets via IAM rules can be a bit tricky at the start, but we ensure Glue has access to AWS S3, Redshift, and other services. Once the role is configured, it runs smoothly. For advanced configurations, connecting to VPCs and setting up connections with JDBC sources takes more time compared to my cloud experience, but overall, for someone with cloud and ETL experience, the setup is manageable and well done.

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Susheel A

Director - Metrics & Analytics at a computer software company with 1,001-5,000 employees

Efficient data warehouse automation with robust features, but may require enhancements in user-friendly self-service options and pricing flexibility for broader corporate appeal

It could enhance its capabilities in the realm of self-service options as currently, it is more suited for individuals with technical proficiency who can create pages using it. When it comes to end users who may lack technical expertise, they are limited to toggling between existing developments. To empower end users to make critical changes without relying heavily on technical expertise, it would be beneficial to introduce more user-friendly features for development and modification. If it could incorporate correlation analysis capabilities into its platform, especially in a user-friendly manner, it would greatly enhance the tool's overall utility and make it an even more outstanding solution. There is a room for improvement regarding stability.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The solution's technical support is good. Whenever we raise a use case where we face an issue in our company, we get a response from the solution's technical team."

"It is a very scalable solution."

"Its ease of use, cost-effectiveness, and highly secure architecture are some of the most valuable features."

"AWS Glue is quite better than other tools, but you have to learn it properly before you start using it."

"AWS Glue's most valuable features are the data catalog, including crawlers and tables, and Glue Studio, which means you don't have to use custom code."

"AWS Glue is a stable and easy-to-use solution."

"The best thing about AWS Glue is its scalability and how easy it is to process a large amount of data."

"I also like that you can add custom libraries like JAR files and use them. So, the ability to use a fast processing engine and embed basic jobs easily are significant advantages."

More AWS Glue pros

"I like modeling and code generation. It has become a pretty handy tool because of its short ideation to delivery time. From the time you decide you are modeling a data warehouse, and once you finish the modeling, it generates all the code, generates all the tables. All you have to do is tick a few things, and you can produce a fully functional warehouse. I also like that they have added all the features I have asked for over four years."

"There were many valuable features, such as extracting any data to put in the cloud. For example, Qlik was able to gather data from SAP and extract SAP data from the platforms."

"The technical support is very good. I rate the technical support a ten out of ten."

"One of the most valuable features of this tool is its automation capabilities, allowing us to design the warehouse in an automated manner. Additionally, we can generate Data Lifecycle Policies (DLP) reports and efficiently implement updates and best practices based on proven design patterns."

"It is a scalable solution."

"As long as you pick the solution that best fits with your requirements, you won't find that performance is a problem. It's good."

"Qlik Compose is good enough. It is user-friendly and intuitive."

"It can scale."

More Qlik Compose pros

Cons

"Only people who can code, either in Java or Python, can use the product freely. Those who don't know Java or Python might find using AWS Glue difficult."

"Not enough resources or services are available to run managed Spark jobs within the solution."

"It is not clear how the partition discovery would have been affected by more data coming in."

"Setting up pipelines is challenging, especially with version control and testing requirements."

"Beginners need additional support as it currently lacks some features required for complex transformations, often necessitating custom Python coding."

"The point for improvement in AWS Glue would be the dynamic allocation of resources while utilizing Lambda functions."

"The solution’s stability could be improved."

"The interface for AWS Glue could improve, they do not put a lot of details."

More AWS Glue cons

"I believe that visual data flow management and the transformation function should be improved."

"The solution has room for improvement in the ETL. They have an ETL, but when it comes to the monitoring portion, Qlik Compose doesn't provide a feature for monitoring."

"My issues with the solution's stability are owing to the fact that it has certain bugs causing issues in some functionalities that should be working."

"It would be better if the first level of technical support were a bit more technically knowledgeable to solve the problem. I think they could also improve the injection of custom scripts. It is pretty difficult to add additional scripts. If the modeling doesn't give you what you want, and you want to change the script generated by the modeling, it is a bit more challenging than in most other products. It is very good with standard form type systems, but if you get a more complicated data paradigm, it tends to struggle with transforming that into a model."

"I don't think Qlik can be used in a high-volume scenario. It didn't work for us."

"When processing data from certain tables with a large volume of data, we encounter significant delays. For instance, when dealing with around one million records, it typically takes three to four hours. To address this, I aim to implement performance improvements across all tables, ensuring swift processing similar to those that are currently complete within seconds. The performance issue primarily arises when we analyze the inserts and updates from the source, subsequently dropping the table. While new insertions are handled promptly, updates are processed slowly, leading to performance issues. Despite consulting our Qlik vendors, they were unable to pinpoint the exact cause of this occurrence. Consequently, I am seeking ways to optimize performance within Qlik Compose, specifically concerning updates."

"Qlik's ETL and data transformation could be better."

"I'd like to have access to more developer training materials."

More Qlik Compose cons

Pricing and Cost Advice

"If you are using the solution for an enterprise business, it will be expensive."

"This solution is affordable and there is an option to pay for the solution based on your usage."

"AWS Glue uses a pay-as-you-go approach which is helpful. The price of the overall solution is low and is a great advantage."

"AWS Glue is a high-priced solution that bills the client $150,000 to $250,000 annually."

"The pricing is a bit higher than other solutions like Athena and EC2. If the pricing becomes more scaled or flexible, it will be good because you have to pay 44 cents just for one DPU for an hour. If you increase DPUs to 5 or 10, the pricing gets multiplied. There are also some time limits like 0 to 10 minutes or 10 to 20 minutes. If the pricing is according to the minutes, it would be better because you have to limit your job to 10 minutes or 20 minutes."

"I rate the product's pricing a five on a scale of one to ten, where one is a high price, and ten is a low price."

"The current cost is around forty to fifty thousand a month."

"Technical support is a paid service, and which subscription you have is dependent on that. You must pay one of them, and it ranges from $15,000 to $25,000 per year."

More AWS Glue pricing and cost advice

"On a scale of one to ten, where one is cheap, and ten is very expensive, I rate the solution a six."

"The price of the solution is expensive."

"While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us."

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Manufacturing Company

Computer Software Company

Comms Service Provider

Financial Services Firm

13%

Comms Service Provider

10%

Construction Company

10%

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	6
Large Enterprise	34

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	3
Large Enterprise	6

Questions from the Community

How do you select the right cloud ETL tool?

AWS Glue and Azure Data factory for ELT best performance cloud services.

See all answers

How does Talend Open Studio compare with AWS Glue?

We reviewed AWS Glue before choosing Talend Open Studio. AWS Glue is the managed ETL (extract, transform, and load) from Amazon Web Services. AWS Glue enables AWS users to create and manage jobs in...

See all answers

What are the most common use cases for AWS Glue?

AWS Glue's main use case is for allowing users to discover, prepare, move, and integrate data from multiple sources. The product lets you use this data for analytics, application development, or ma...

See all answers

Which ETL tool would you recommend to populate data from OLTP to OLAP?

There are two products I know about * TimeXtender : Microsoft based, Transformation logic is quiet good and can easily be extended with T-SQL , Has a semantic layer that generates metat data for cu...

See all answers

Comparisons

AWS Database Migration Service vs AWS Glue

Compared 41% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs AWS Glue

Compared 6% of the time

SSIS vs AWS Glue

Compared 4% of the time

Palantir Foundry vs AWS Glue

Compared 3% of the time

Amazon Data Firehose vs AWS Glue

Compared 3% of the time

More AWS Glue Competitors

Qlik Replicate vs Qlik Compose

Compared 10% of the time

AWS Database Migration Service vs Qlik Compose

Compared 9% of the time

SSIS vs Qlik Compose

Compared 8% of the time

Qlik Talend Cloud vs Qlik Compose

Compared 8% of the time

WhereScape RED vs Qlik Compose

Compared 6% of the time

More Qlik Compose Competitors

Product Reports

Buyer's Guide

AWS Glue

August 2026

Download AWS Glue product report

Buyer's Guide

Qlik Compose

July 2026

Download Qlik Compose product report

Also Known As

No data available

Compose, Attunity Compose

Overview

AWS Glue is a serverless data integration service offering seamless integration with AWS services like S3, Redshift, and Athena. Known for its flexibility with data formats and automation of ETL tasks, AWS Glue enhances data management and transformation.

AWS Glue facilitates seamless data extraction, transformation, and loading for businesses, integrating with key AWS services, allowing efficient data pipeline automation. It's valued for a user-friendly GUI, scalability, and cost-effectiveness, supporting PySpark for complex datasets and includes a robust data catalog, real-time backup capabilities, and code generation. Despite its strengths, improvements are needed in documentation, training, and broader programming language support. Users face challenges with its complex interface and integration with non-AWS products, driving demand for enhancements in its usability and performance.

What are AWS Glue's most important features?

Seamless AWS Integration: Connects effortlessly with services like S3, Redshift, and Athena.
Serverless Operation: Removes the need for infrastructure management.
Flexible Data Format Handling: Supports various data formats for comprehensive data management.
User-Friendly GUI: Simplifies the creation and management of ETL jobs.
Data Catalog: Provides an organized repository for metadata management.
Real-Time Data Backup: Ensures data integrity and availability.
Code Generation: Facilitates easy script generation for data processes.

What benefits or ROI should users look for in reviews?

Cost Efficiency: Reduced operational costs through serverless architecture.
High Performance: Efficient data processing and transformation capabilities.
Scalability: Adapts to businesses' evolving data demands.
Ease of Use: Intuitive interface allowing streamlined ETL workflows.
Automation: Simplified data pipeline tasks saving time and effort.

Businesses leverage AWS Glue in industries for ETL processes, data integration, and transformation. It is used to optimize data lakes or warehouses integration, enhancing data cataloging and real-time integration. Its serverless feature enables efficient data processing in sectors like finance and healthcare, where handling complex data-intensive tasks is crucial.

Amazon Web Services (AWS)

Qlik Compose enhances data management with ETL capabilities, data integration with CDC, and real-time replication. Its intuitive interface enables easy data modeling and automation, supporting various database integrations.

Qlik Compose is designed for efficient data preparation, migration, and warehouse generation. It incorporates ETL functionalities and data integration with CDC, allowing users to effortlessly create data marts without code. Its automation features facilitate warehouse design while graphical representations and connectivity options increase versatility across multiple sources. Users value its stability, scalability, and the support provided, although improvements in ETL functionalities, performance for large datasets, and NoSQL integration are needed. The solution is widely used in business intelligence with tools like Qlik Replicate for real-time data replication and requires direct SQL for complex transformations.

What are the key features of Qlik Compose?

ETL Capabilities: Simplifies data extraction, transformation, and loading
Data Integration with CDC: Enables real-time data replication
Intuitive Interface: Facilitates easy data modeling and automation
Drag-and-Drop Functionality: Streamlines data task management
Auto-Mapping: Enhances integration of multiple data sources
No-Code Data Marts Creation: Reduces dependency on technical skills

What benefits should users consider in the reviews?

Stability and Scalability: Reliable functioning for growing data needs
Technical Support: Availability of assistance for troubleshooting
Real-Time Replication Capabilities: Efficient data processing and analytics
Low-Code Development: Simplifies complex data handling processes

In industries, Qlik Compose is implemented for enhancing data preparation, migration, and warehousing. It is used in small projects or straightforward data integration tasks and supports business intelligence efforts by offering low-code capabilities, enabling companies to deliver tailored analytics solutions efficiently.

Qlik

Sample Customers

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

Poly-Wood

Buyer's Guide

Cloud Data Integration

July 2026

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