"Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs."
"Data catalog and triggers are the two best features for me. AWS Glue has its own data catalog, which makes it great and really easy to use. Triggers are also really good for scheduling the ETL process."
"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."
"It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly."
"The key role for Glue is that it hosts our metadata before rolling out our actual data. This is the major advantage of using this solution and our clients client have been very satisfied with it."
"Its user interface is quite good. You just need to choose some options to create a job in AWS Glue. The code-generation feature is also useful. If you don't want to customize it and simply want to read a file and store the data in the database, it can generate the code for you."
"I like that it's flexible, powerful, and allows you to write your own queries and scripts to get the needed transformations."
"The facility to integrate with S3 and the possibility to use Jupyter Notebook inside the pipeline are the most valuable features."
"I have found it to be a very good, stable, and strong product."
"Qlik Compose is good enough. It is user-friendly and intuitive."
"Currently, it supports only two languages in the background: Python and Scala. From our customization point of view, it would be helpful if it can also support Java in the background."
"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 crucial problem with AWS Glue is that it only works with AWS. It is not an agnostic tool like Pentaho. In PowerCenter, we can install the forms from Google and other vendors, but in the case of AWS Glue, we can only use AWS."
"There should be more connectors for different databases."
"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."
"Overall, I consider the technical support to be fine, although the response time could be faster in certain cases."
"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."
"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."
AWS Glue is ranked 2nd in Cloud Data Integration with 9 reviews while Qlik Compose is ranked 41st in Data Integration Tools with 2 reviews. AWS Glue is rated 8.2, while Qlik Compose is rated 6.0. The top reviewer of AWS Glue writes "Easy to perform ETL on multiple data sources, and easy to use after you learn it". On the other hand, the top reviewer of Qlik Compose writes "It's an intuitive solution for doing basic transformations, but it cannot handle high volumes". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, Talend Open Studio, Informatica Cloud Data Integration and SSIS, whereas Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, Palantir Foundry, WhereScape RED and Informatica PowerCenter.
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