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."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."
"We no longer had to worry much about infrastructure management because AWS Glue is serverless, and Amazon takes care of the underlying infrastructure."
"The solution is stable and reliable."
"AWS Glue is quite better than other tools, but you have to learn it properly before you start using it."
"I like its integration and ability to handle all data-related tasks."
"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."
"It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly."
"I think Talend is one of the easiest tools for faster implementation compared to other tools."
"They're very competitive in terms of performance, which is a good selling point. It has very rich features. It provides a very rich feature set in the application."
"We can develop our own code if we do not see the functionality we need."
"The availability of connectors is great."
"The basic tools are easy to pick up and understand."
"The most valuable feature is the data loading and scripting language"
"The most valuable features of the Talend Data Management Platform are the components."
"The most valuable feature is integration."
"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."
"I haven't looked into Glue in terms of seeking out flaws. I've not come across missing features."
"On occasion, the solution's dashboard reports that a project failed due to runtime but it actually succeeded."
"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."
"The product has only a few built-in transformations."
"AWS Glue is more costly compared to other tools like Airflow."
"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 product must enhance the data quality."
"I'd be interested in seeing the running of Python programs and transformations from within the studio itself."
"We'd like to see more connectors it the future."
"I've had some issues with bugs causing crashes, especially when making changes to the system or with the monthly upgrades to Studio they've introduced."
"The solution's memory sometimes bottlenecks and that can be challenging."
"The sales and market department could improve the Talend Data Management Platform."
"The stability is good, but the performance is slower when I work on a huge amount of data."
"Once you get past the basic tools, it gets pretty complicated."
More Talend Data Management Platform Pricing and Cost Advice →
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Talend Data Management Platform is ranked 22nd in Data Integration with 17 reviews. AWS Glue is rated 7.8, while Talend Data Management Platform is rated 8.4. 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, SSIS, Informatica Cloud Data Integration 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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