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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 (36th)
 

Featured Reviews

Saurabh Jaiswal - PeerSpot reviewer
Enables seamless integration and data preparation with robust transformation capabilities
AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models. It offers transformation options on canvas or through ETL pipelines, notebooks, and code. Additionally, it supports data preparation, cleaning, and filtering seamlessly. AWS Glue also enhances job scheduling and orchestration capabilities, integrating with AWS Glue Studio for comprehensive data workflow management.
Sahil Taneja - PeerSpot reviewer
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

"It's very good to manage."
"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."
"It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly."
"I like that it's flexible, powerful, and allows you to write your own queries and scripts to get the needed transformations."
"I appreciate AWS Glue for its cost-effectiveness."
"For ETL, I feel the performance is excellent."
"AWS Glue has reduced efforts by 60%, which is the main benefit."
"AWS Glue's best features are scalability and cloud-based features."
"I have found it to be a very good, stable, and strong product."
"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."
"It can scale."
"The technical support is very good. I rate the technical support a ten out of ten."
"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."
"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 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's a stable solution."
 

Cons

"It fails to handle massive databases acquired from various sources."
"I have encountered challenges with multi-region support."
"I haven't looked into Glue in terms of seeking out flaws. I've not come across missing features."
"The solution's visual ETL tool is of no use for actual implementation."
"In terms of improvement, the performance of AWS Glue could be faster."
"AWS Glue is more costly compared to other tools like Airflow."
"It would be better if it were more user-friendly. The interesting thing we found is that it was a little strange at the beginning. The way Glue works is not very straightforward. After trying different things, for example, we used just the console to create jobs. Then we realized that things were not working as expected. After researching and learning more, we realized that even though the console creates the script for the ETL processes, you need to modify or write your own script in Spark to do everything you want it to do. For example, we are pulling data from our source database and our application database, which is in Aurora. From there, we are doing the ETL to transform the data and write the results into Redshift. But what was surprising is that it's almost like whatever you want to do, you can do it with Glue because you have the option to put together your own script. Even though there are many functionalities and many connections, you have the opportunity to write your own queries to do whatever transformations you need to do. It's a little deceiving that some options are supposed to work in a certain way when you set them up in the console, but then they are not exactly working the right way or not as expected. It would be better if they provided more examples and more documentation on options."
"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."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
"I believe that visual data flow management and the transformation function should be improved."
"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."
"There should be proper documentation available for the implementation process."
"Qlik's ETL and data transformation could be better."
"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."
"I'd like to have access to more developer training materials."
"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."
 

Pricing and Cost Advice

"I would rate the solution a six or seven on a scale of one to ten, with ten being very expensive. Specifically, I rate its pricing a six out of ten."
"This solution is affordable and there is an option to pay for the solution based on your usage."
"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 overall cost of AWS Glue could be better. It cost approximately $1,000 a month. There is paid support available from AWS Glue."
"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."
"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."
"AWS Glue follows a pay-as-you-go model, wherein the cost of the data you use will be counted as a monthly bill."
"If you are using the solution for an enterprise business, it will be expensive."
"On a scale of one to ten, where one is cheap, and ten is very expensive, I rate the solution a six."
"While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us."
"The price of the solution is expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
21%
Computer Software Company
12%
Manufacturing Company
8%
Government
6%
Financial Services Firm
16%
Government
10%
Manufacturing Company
10%
Insurance Company
6%
 

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...
What do you like most about Qlik Compose?
The most valuable is its excellence as a graphical data representation tool and the versatility it offers, especially with drill-down capabilities.
What is your experience regarding pricing and costs for Qlik Compose?
While they outperform Tableau, there's room for improvement in Qlik's pricing structures, especially for corporate clients like us.
 

Also Known As

No data available
Compose, Attunity Compose
 

Overview

 

Sample Customers

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