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AWS Glue vs Qlik Compose comparison

 

Comparison Buyer's Guide

Executive Summary

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
50
Ranking in other categories
Cloud Data Integration (1st)
Qlik Compose
Average Rating
7.6
Reviews Sentiment
6.5
Number of Reviews
12
Ranking in other categories
Data Integration (47th)
 

Featured Reviews

SC
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.
Sahil Taneja - PeerSpot reviewer
Principal Consultant/Manager at Tenzing
Easy matching and reconciliation of data
The initial setup was easy for the data warehousing concept. But for a person who is new to ETL and warehousing concepts, it may take some time. If someone is familiar with these concepts, they could understand and learn the tool quickly. However, compared to other tools, the UI is complex. It would be helpful to have a better UI and documentation for new users. As of now, there is a challenge in learning the Compose tool for new users altogether. Qlik Compose was deployed on-premises. But the servers, like the SQL servers were maintained on the cloud—the managed instances.

Quotes from Members

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

Pros

"The AWS Glue Data Catalog provides metadata management and schema discovery. AWS Glue simplifies data transformation with automatic schema detection, incremental data updates, and integration with other AWS services."
"You do not need many frameworks to run Glue."
"It's very good to manage."
"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."
"The solution is stable and reliable."
"I like its integration and ability to handle all data-related tasks."
"Transformations are valuable because you can modify or override complex data logic from an open source or Spark to solve issues."
"AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models."
"It can scale."
"It is a scalable solution."
"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."
"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."
"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."
"I have found it to be a very good, stable, and strong product."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"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."
 

Cons

"If there's a cluster-related configuration, we have to make worker notes, which is quite a headache when processing a large amount of data."
"There is a learning curve to this tool."
"The mapping area and the use of the data catalog from Glue could be better."
"The solution could be cheaper. The price of the solution is an area that needs improvement."
"The product is expensive for data streaming. This area needs improvement."
"The technical support for this solution could be improved. In future, we would like to connect more services like Athena or Kinesis to help control more loads of data."
"It is not clear how the partition discovery would have been affected by more data coming in."
"The point for improvement in AWS Glue would be the dynamic allocation of resources while utilizing Lambda functions."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"I'd like to have access to more developer training materials."
"There could be more customization options."
"For more complex work, we are not using Qlik Compose because it cannot handle very high volumes at the moment. It needs the same batching capabilities that other ETL tools have. We can't batch the data into small chunks when transforming large amounts of data. It tries to do everything in one shot and that's where it fails."
"I believe that visual data flow management and the transformation function should be improved."
"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."
"Qlik's ETL and data transformation could be better."
"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."
 

Pricing and Cost Advice

"It is an expensive product. I rate its pricing a nine out of ten."
"If you are using the solution for an enterprise business, it will be expensive."
"I rate the tool's pricing a four out of ten."
"The current cost is around forty to fifty thousand a month."
"AWS Glue is quite costly, especially for small organizations."
"It is not expensive. AWS Glue works on the serverless architecture. We get charged for the time the server is up. For our use case, we have to use it once in a day, and it is not expensive for us."
"Its price is good. We pay as we go or based on the usage, which is a good thing for us because it is simple to forecast for the tool. It is good in terms of the financial planning of the company, and it is a good way to estimate the cost. It is also simple for our clients. In my opinion, it is one of the best tools in the market for ETL processes because of the fact that you pay as you use, which separates it from other big tools such as PowerCenter, Pentaho Data Integration, and Talend."
"I rate pricing an eight out of ten."
"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
19%
Computer Software Company
11%
Manufacturing Company
8%
Government
6%
Government
12%
Financial Services Firm
12%
Manufacturing Company
10%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise6
Large Enterprise32
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise3
Large Enterprise6
 

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.
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...
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...
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...
 

Also Known As

No data available
Compose, Attunity Compose
 

Overview

 

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
Poly-Wood
Find out what your peers are saying about AWS Glue vs. Qlik Compose and other solutions. Updated: March 2026.
883,824 professionals have used our research since 2012.