We performed a comparison between AWS Glue and ETL Solutions Transformation Manager 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."We no longer had to worry much about infrastructure management because AWS Glue is serverless, and Amazon takes care of the underlying infrastructure."
"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."
"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."
"AWS Glue is a stable and easy-to-use solution."
"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."
"It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly."
"One of the best features of the solution is its ability to easily integrate with other AWS services."
"The solution helps organizations gain flexibility in defining the structure of the data."
"It is among the best, even if not widely known."
"Back in the day, we could only get reports and analyze what happened after the fact, but today now we can generate real-time insights. Transformation Manager feeds your data science projects. We generate models and then give them to the clients, so they can come up with real-time predictions and recommendations in addition to reporting."
"It is a reliable solution."
"Overall, I consider the technical support to be fine, although the response time could be faster in certain cases."
"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."
"The mapping area and the use of the data catalog from Glue could be better."
"While working on AWS Glue, I could not find any training material for it."
"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."
"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."
"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."
"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."
"There is room for improvement in the solution's visualization tool."
"Transformation Manager reporting could be better. There are better options for reporting tools these days. We use Microsoft BI sometimes, but Tableau is becoming too expensive. Microsoft BI's visualization features are maturing."
"They should build a functional architecture based on queuing."
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AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while ETL Solutions Transformation Manager is ranked 32nd in Data Integration with 3 reviews. AWS Glue is rated 7.8, while ETL Solutions Transformation Manager is rated 9.0. 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 ETL Solutions Transformation Manager writes "It lets us create models so we can generate real-time predictions and insights for a our clients". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Informatica Cloud Data Integration and Talend Open Studio, whereas ETL Solutions Transformation Manager is most compared with webMethods Integration Server, Axway AMPLIFY Application Integration, TIBCO Spotfire, Altair Monarch and Denodo. See our AWS Glue vs. ETL Solutions Transformation Manager report.
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