We performed a comparison between AWS Glue and Qlik Replicate 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 a good solution for developers, they have the ability to write code in different languages and other software."
"AWS Glue is a stable and easy-to-use solution."
"I like that it's flexible, powerful, and allows you to write your own queries and scripts to get the needed transformations."
"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."
"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."
"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 appreciate AWS Glue for its cost-effectiveness."
"It's very user-friendly when it comes to settings and configuration. It also offers very detailed logging about warnings and errors."
"Great with replicating and updating records."
"Support has been great."
"We use Qlik Replicate to change data capture of databases in production environments."
"The CDC and the flexibility to use QVD as a source are the most valuable features of Qlik Replicate."
"Low-priced reporting and analytics solution, with good scalability and stability. It has on-premises and cloud versions that are cohesive and can integrate well."
"The main valuable feature is its real-time change data capture (CDC) capabilities, which process data with minimal latency. There is not much delay. It also performs well with batch-wise data applications."
"Qlik Replicate stands out with its cutting-edge technology and its ability to handle diverse data management tasks. This powerful tool allows us to efficiently and swiftly load data into various data stores or destinations, while also enabling easy distribution across different endpoints. A notable feature is its capability to reload data from multiple sources by creating multiple tasks within a brief timeframe of fifteen to twenty minutes. This eliminates the need for manual intervention and ensures quick data loading from different tables."
"On occasion, the solution's dashboard reports that a project failed due to runtime but it actually succeeded."
"The solution could be cheaper. The price of the solution is an area that needs improvement."
"The solution should offer features for streaming data in addition to batching data."
"It fails to handle massive databases acquired from various sources."
"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 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 solution's visual ETL tool is of no use for actual implementation."
"Some features can also be overly dependent on each other. So, there is room for improvement."
"Support-wise, this solution is in need of improvement."
"In various scenarios, an important consideration is when we encounter issues and Qlik Replicate suggests reloading a specific table. If we face any problems or encounter errors with that table, it becomes necessary to make a change in Qlik Replicate. Performing a full reload every time is not feasible or practical. Instead, we should identify the specific issues and address them without repeating the entire reloading process. Based on this approach, we can investigate and resolve the problem by performing targeted loads from the source itself. This change aligns with my perspective and is something I would like to implement."
"It would be better if the solution’s pricing were more obvious."
"In the next release, I would like to see closer integration with data catalyst."
"Support for this product is not great. It needs to be improved."
"When you remote into it the Qlik Replicate UI a lot of times it just freezes. We set up the EC2, to allow them to go to the server and click on the Replicate icon, it just opens up and just sits there. At that point, we have to go into the EC2 and then reboot the server. This should be fixed, it is frustrating."
"The solution's flexibility to work with APIs should also be improved since it is very weak in working with APIs."
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Qlik Replicate is ranked 16th in Data Integration with 13 reviews. AWS Glue is rated 7.8, while Qlik Replicate is rated 8.2. 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 Replicate writes " Performs well with batch-wise data applications but some features can also be overly dependent on each other". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Informatica Cloud Data Integration and Talend Open Studio, whereas Qlik Replicate is most compared with Oracle GoldenGate, AWS Database Migration Service, Qlik Compose, Azure Data Factory and Informatica Cloud Data Integration. See our AWS Glue vs. Qlik Replicate report.
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