We performed a comparison between AWS Glue and Qlik Compose based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."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."
"Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs."
"AWS Glue's best features are scalability and cloud-based features."
"It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly."
"The most valuable feature of AWS Glue is scalability."
"AWS Glue is quite better than other tools, but you have to learn it properly before you start using it."
"AWS Glue is a stable and easy-to-use solution."
"Our entire use case was very easily handled or solved using this solution."
"One of the most valuable features was the ability to integrate multiple source systems that mainly used structured IDBMS versions."
"It is a scalable solution."
"It's a stable solution."
"It can scale."
"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."
"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."
"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."
"In terms of improvement, the performance of AWS Glue could be faster."
"The solution's visual ETL tool is of no use for actual implementation."
"There should be more connectors for different databases."
"While working on AWS Glue, I could not find any training material for it."
"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."
"Cost-wise, AWS Glue is expensive, so that's an area for improvement. The process for setting up the solution was also complex, which is another area for improvement."
"AWS Glue is more costly compared to other tools like Airflow."
"The solution’s stability could be improved."
"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."
"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."
"There could be more customization options."
"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."
"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."
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Qlik Compose is ranked 18th in Data Integration with 12 reviews. AWS Glue is rated 7.8, while Qlik Compose is rated 7.6. The top reviewer of AWS Glue writes "Provides serverless mechanism, easy data transformation and automated infrastructure management". On the other hand, the top reviewer of Qlik Compose writes "Easy matching and reconciliation of data". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Informatica Cloud Data Integration and Talend Open Studio, whereas Qlik Compose is most compared with Qlik Replicate, Talend Open Studio, Azure Data Factory, SSIS and Oracle Data Integrator (ODI). See our AWS Glue vs. Qlik Compose report.
See our list of best Cloud Data Integration vendors.
We monitor all Cloud Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.