We performed a comparison between AWS Glue and Talend Data integration 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."I like the fact that AWS Glue works with Python scripts."
"AWS Glue is quite better than other tools, but you have to learn it properly before you start using it."
"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."
"It's fairly straightforward as a product; it's not very complicated."
"AWS Glue is a stable and easy-to-use solution."
"Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs."
"I also like that you can add custom libraries like JAR files and use them. So, the ability to use a fast processing engine and embed basic jobs easily are significant advantages."
"Our entire use case was very easily handled or solved using this solution."
"Talend Data integration has a wide library of connectors."
"The product's integration with PostgreSQL and Jira has been helpful for us. Its performance is good. However, we do not use it for large data sets."
"I'm very passionate about this solution because if you look at any other tool that costs around $200 - $300,000, like Delphix which costs you a million dollars, Talend is very cheap and is almost is at par with what others can do. There is one thing which Delphix does which Talend cannot do, but overall, I would say apart from that, if you're looking for a solution, you should give it a try."
"We have multiple use cases for this solution. We integrate with Salesforce, SAP and Oracle databases to build business logic and provide reporting."
"The crucial problem with AWS Glue is that it only works with AWS. It is not an agnostic tool like Pentaho. In PowerCenter, we can install the forms from Google and other vendors, but in the case of AWS Glue, we can only use AWS."
"In terms of performance, if they can further optimize the execution time for serverless jobs, it would be a welcome improvement."
"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."
"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 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."
"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."
"I have encountered challenges with multi-region support."
"There are no concurrent licenses, they only have seat licenses on cloud. That's the whole challenge. For example, if in any project your headcount increases or decreases, you do not have that concurrence and you have a seat license, you run into challenges because you have to procure a few more licenses for getting the job done."
"Due to using the open-source version of Talend Data Integration, which lacks a scheduler, our current approach involves developing jobs in Talend, exporting them as Java packages, and utilizing an external scheduler, such as Windows Scheduler, to manage the scheduling process."
"Sometimes there are bugs which are unidentified and we have to follow-up with the Talend team to resolve them. In a critical situation, it takes time for them to update patches."
"The tool's technical support needs to be better. It doesn't have a local data center but pushes everything to the cloud. They need to check in with customers to see if they're happy and how well the solutions work. They need to assign a customer success manager for the accounts they sell."
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Talend Data integration is ranked 23rd in Cloud Data Integration with 4 reviews. AWS Glue is rated 7.8, while Talend Data integration is rated 8.0. 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 Talend Data integration writes "Very affordable and on par with much more expensive solutions". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Informatica Cloud Data Integration and Talend Open Studio, whereas Talend Data integration is most compared with Talend Open Studio, SAP Cloud Platform, Oracle Data Integrator (ODI) and Microsoft Azure Logic Apps. See our AWS Glue vs. Talend Data integration report.
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