We performed a comparison between AWS Glue and Informatica Cloud Data Integration based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: For users vested in the AWS ecosystem, AWS is hands down the best choice. Informatica Cloud Data Integration is flexible and allows users to decide how to distribute their IPUs in their own networks. Data residency laws make it challenging to choose this solution, as their regions are currently very limited.
"I appreciate AWS Glue for its cost-effectiveness."
"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."
"We have found it beneficial when moving data from one source to another."
"The product has a valuable feature for data catalog."
"The facility to integrate with S3 and the possibility to use Jupyter Notebook inside the pipeline are the most valuable features."
"One of the best features of the solution is its ability to easily integrate with other AWS services."
"The most valuable feature of AWS Glue is its ease of use and good documentation. Additionally, we can do all the transformations that we need."
"The solution's technical support is good. Whenever we raise a use case where we face an issue in our company, we get a response from the solution's technical team."
"I like the fact that you can find almost any product connection that you need and the list is always expanding."
"It is one of the best tools available for data integration."
"The solution provides increased efficiency while still being user-friendly and easy to operate."
"Replication allows us to fully replicate all objects from Shop Floor Data Collection (SFDC) to in-house/on-premises database in one job."
"Their new licensing is very flexible. With Informatica Cloud, you have plenty of items under the same umbrella, such as services, offerings, data quality, and data masking. You have also got master data management and API management. What I really like about them is that you don't need to go to Informatica and say that you need a data integration module. You would say that you need iPaaS or Informatica Cloud. They'll then try to understand your needs and give you IPUs, which are the processing units. If I purchased a hundred IPUs from Informatica as a customer, I can use 70 IPUs for data integration. I would also need data quality, so I can use 10 IPUs for data quality. I can use the remaining 20 IPUs for API management. Down the line, if I see that my initial data integration needs for the development phase are met, then out of the 70 IPUs assigned for data integration, I can use 30 IPUs for data masking. I can shuffle these numbers in any way within the Informatica Cloud umbrella for the tenure for which I have subscribed to these IPUs. I can use all services the way I want. This flexibility is what I really love about Informatica. It also has got good connectors."
"Data integration is the most valuable feature. The ability to connect to any of the sources and enterprise applications makes our lives easier."
"REST API: Excellent for scripting control and reporting mechanisms"
"The program is stable and scalable."
"It is not clear how the partition discovery would have been affected by more data coming in."
"The mapping area and the use of the data catalog from Glue could be better."
"The solution’s stability could be improved."
"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."
"While working on AWS Glue, I could not find any training material for it."
"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."
"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."
"In terms of performance, if they can further optimize the execution time for serverless jobs, it would be a welcome improvement."
"The current features are a bit complicated, and we need to write big scripts and test."
"It would be helpful if there was a GenAI feature integrated into the system, especially regarding the data quality."
"Informatica Cloud Data Integration could improve the price by making it less expensive."
"There may be some types of limitations with the performance."
"I would like to see more functionality added so that it is a bit closer to how much you can do with Informatica PowerCenter."
"One area that needs to improve is the user experience because it is very complex. The trial version is very complex so it's not easy to start using the program immediately. You must study the rules first."
"With the solution, we had some issues, and we have every day, and we used to open a ticket. Sometimes, there are data issues and transformation issues."
"It could be improved by including a buffer that saves data when there is a connectivity issue."
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AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Informatica Cloud Data Integration is ranked 5th in Cloud Data Integration with 40 reviews. AWS Glue is rated 7.8, while Informatica Cloud Data Integration is rated 7.8. 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 Informatica Cloud Data Integration writes "A stable, scalable, and user-friendly solution". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Talend Open Studio and Oracle Integration Cloud Service, whereas Informatica Cloud Data Integration is most compared with Informatica PowerCenter, Azure Data Factory, Fivetran, IBM Cloud Pak for Data and Mule Anypoint Platform. See our AWS Glue vs. Informatica Cloud Data Integration report.
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