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AWS Glue vs Qlik Compose comparison

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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 (55th)
 

Featured Reviews

NS
Principal Consultant at a retailer with 1,001-5,000 employees
The solution improves ETL performance but faces challenges with version upgrades
For ETL, I feel the performance is excellent. If I create jobs in a standard way, the performance is great, and maintenance is also seamless. It is serverless, so I do not need to worry about other integrations. It runs on a serverless VM. Glue services from AWS are regularly upgraded with new properties and functions. We use PySpark and other frameworks, which help customize our ETL process in a standard way. During our process, we utilized the typical SQL ITIL process standard in Glue-oriented ETL services, which helped us improve performance and time. AWS running time, mostly during the morning, saved us time compared to the old ETL method. There are many email notifications once a job is successful or fails, and we get notifications using SES or AWS's Simple Notification Service. Glue is integrated with both email alerts, and we are responsible for managing the full data journey from end to end.
SA
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.

Quotes from Members

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

Pros

"We have found it beneficial when moving data from one source to another."
"AWS Glue is fast and managed by AWS. Hence, you don't have to worry about capacity and the performance of Glue jobs. It has integrations with other data stores of AWS. The product offers metadata management, logging, and ETL processing capabilities. It comes with a powerful feature, Glue Studio, which helps to do queries interactively within the community. It is a managed service and very secure. Another popular and mature service is S3."
"AWS Glue is very quick to start without cold starts, unlike AWS Lambda."
"AWS Glue is a good solution for developers, they have the ability to write code in different languages and other software."
"AWS Glue's best features are scalability and cloud-based features."
"Transformations are valuable because you can modify or override complex data logic from an open source or Spark to solve issues."
"It is a stable and scalable solution."
"The solution is highly user-friendly, and its features are easy to use. The new addition of AWS Glue Data Catalog is also very beneficial, making the tool even more helpful for its users."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"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's a stable 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."
"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."
"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."
"The technical support is very good. I rate the technical support a ten out of ten."
"I have found it to be a very good, stable, and strong product."
 

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 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."
"One area that could be improved is the ETL view. The drag-and-drop interface is not as user-friendly as some other ETL tools."
"Beginners need additional support as it currently lacks some features required for complex transformations, often necessitating custom Python coding."
"It is not clear how the partition discovery would have been affected by more data coming in."
"The start-up time is really high right now. For instance, when you start up a new job, you have to wait for five or eight minutes before it starts. If the start-up time is reduced to one or two minutes, it will be great. It will be better to have a direct linkage to Redshift in AWS. If we can use data catalogs from Redshift, it will be so easy to create some data catalogs. Currently, we can only use data catalogs from S3."
"The mapping area and the use of the data catalog from Glue 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 believe that visual data flow management and the transformation function should be improved."
"There could be more customization options."
"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."
"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."
"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."
"I don't think Qlik can be used in a high-volume scenario. It didn't work for us."
"There is some scope for improvement around the documentation, and a better UI would definitely help."
 

Pricing and Cost Advice

"I rate the tool's pricing a four out of ten."
"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."
"I rate pricing an eight out of ten."
"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."
"AWS Glue is a paid service that doesn't come under the free trial of AWS."
"The current cost is around forty to fifty thousand a month."
"AWS Glue follows a pay-as-you-go model, wherein the cost of the data you use will be counted as a monthly bill."
"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."
"On a scale of one to ten, where one is cheap, and ten is very expensive, I rate the solution a six."
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Top Industries

By visitors reading reviews
Financial Services Firm
18%
Manufacturing Company
8%
Comms Service Provider
7%
Computer Software Company
6%
Financial Services Firm
11%
Construction Company
10%
Comms Service Provider
10%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise5
Large Enterprise34
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
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