We performed a comparison between AWS Glue and Palantir Foundry 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 solution integrates well with other AWS products or services."
"The most valuable feature for me is the visual interface of AWS Glue."
"I like the fact that AWS Glue works with Python scripts."
"I like its integration and ability to handle all data-related tasks."
"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."
"AWS Glue is quite better than other tools, but you have to learn it properly before you start using it."
"The solution helps organizations gain flexibility in defining the structure of the data."
"I appreciate AWS Glue for its cost-effectiveness."
"The interface is really user-friendly."
"It's scalable."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"The data lineage is great."
"Great features available in one tool."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"The ease of use is my favorite feature. We're able to build different models and projects or combine different projects to build one use case."
"The interface for AWS Glue could improve, they do not put a lot of details. You can write the code, in PySpark or in Scala, which is a big advantage, it is only easy to use for a developer. It will be difficult for new users to enter the cloud environment."
"If there's a cluster-related configuration, we have to make worker notes, which is quite a headache when processing a large amount 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."
"AWS Glue is more costly compared to other tools like Airflow."
"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."
"We face performance issues when using AWS Glue for data transformation and integration."
"It is not clear how the partition discovery would have been affected by more data coming in."
"AWS Glue would be improved by making it easier to switch from single to multi-cloud."
"If you want to create new models on specific data sets, computing that is quite costly."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"Difficult to receive data from external sources."
"Cost of this solution is quite high."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"They do not have a data center in Europe, and we have lots of personally identifiable information in our dataset that needs to be hosted by a third-party data center like Amazon or Microsoft Azure."
"The workflow could be improved."
AWS Glue is ranked 1st in Cloud Data Integration with 37 reviews while Palantir Foundry is ranked 12th in Cloud Data Integration with 14 reviews. AWS Glue is rated 7.8, while Palantir Foundry is rated 7.6. 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 Palantir Foundry writes "The data visualization is fantastic and the security is excellent". AWS Glue is most compared with AWS Database Migration Service, Informatica PowerCenter, SSIS, Informatica Cloud Data Integration and Denodo, whereas Palantir Foundry is most compared with Azure Data Factory, Palantir Gotham, SAP Data Services, Alteryx Designer and Denodo. See our AWS Glue vs. Palantir Foundry report.
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