We performed a comparison between AWS Glue and Talend Data Management Platform 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 have found it beneficial when moving data from one source to another."
"The most valuable feature for me is the visual interface of AWS Glue."
"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."
"One of the best features of the solution is its ability to easily integrate with other AWS services."
"The most valuable features currently are glue studio, jobs, and triggers."
"I appreciate AWS Glue for its cost-effectiveness."
"I like its integration and ability to handle all data-related tasks."
"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."
"The most valuable feature is the data loading and scripting language"
"The solution can run on any machine and that is a big advantage."
"Talend Studio has the ability to connect to almost anything to integrate data from files, databases, web services, etc."
"The solution is connected to various phones. It retrieves the configuration from the system."
"The most valuable feature is integration."
"I like the way that you can use the context variables, and how you can work those context variables to give you values and settings for every development environment, such as PROD, TEST, and DEV."
"The features that I like the most are the simplicity of the interface, and the ability to quickly develop with a predefined component."
"I think Talend is one of the easiest tools for faster implementation compared to other tools."
"AWS Glue is more costly compared to other tools like Airflow."
"Glue could perform better. It sometimes takes too long to test a Glue job. Google Cloud Platform offers more Python scripts than AWS."
"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."
"The solution should offer features for streaming data in addition to batching data."
"The product is expensive for data streaming. This area needs improvement."
"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."
"It is not clear how the partition discovery would have been affected by more data coming in."
"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."
"We'd like to see more connectors it the future."
"I would like to sync a project and do an upload from that current version, and then from GitLab, be able to download the latest one."
"The sales and market department could improve the Talend Data Management Platform."
"I'd be interested in seeing the running of Python programs and transformations from within the studio itself."
"I think they should drive toward AI and machine learning. They could include a machine-learning algorithm for the deduplication."
"Performance and speed could be improved."
"Including either XML or JSON in the next release would definitely be a good transformation. I'm not sure if Talend has that feature, but it's one of those requirements that we are working around and have to do some parsing of XML so this could make it easier."
"The documentation from version to version could be more accurate."
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AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Talend Data Management Platform is ranked 21st in Data Integration with 18 reviews. AWS Glue is rated 7.8, while Talend Data Management Platform 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 Talend Data Management Platform writes "Built for everything and packed with features but there are some monitoring limitations". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, Informatica Cloud Data Integration, SSIS and Talend Open Studio, whereas Talend Data Management Platform is most compared with Talend Open Studio, Talend Data Fabric, SAP Data Services, Collibra Catalog and SSIS. See our AWS Glue vs. Talend Data Management Platform report.
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