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."AWS Glue is fast and managed by AWS. Hence, you don't have to worry about capacity and the performance of Glue jobs. It has integrations with other data stores of AWS. The product offers metadata management, logging, and ETL processing capabilities. It comes with a powerful feature, Glue Studio, which helps to do queries interactively within the community. It is a managed service and very secure. Another popular and mature service is S3."
"I like its integration and ability to handle all data-related tasks."
"It is AWS-integrated. There is end-to-end integration with the other AWS services. It is also user-friendly."
"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."
"It is a stable and scalable solution."
"One of the best features of the solution is its ability to easily integrate with other AWS services."
"Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs."
"It's fairly straightforward as a product; it's not very complicated."
"The AI engine that comes with Palantir Foundry is quite interesting."
"It's scalable."
"The solution offers very good end-to-end capabilities."
"The security is also excellent. It's highly granular, so the admins have a high degree of control, and there are many levels of security. That worked well. You won't have an EDC unless you put everything onto the platform because it is its own isolated thing."
"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."
"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."
"The price of the solution could improve."
"In terms of improvement, the performance of AWS Glue could be faster."
"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."
"I would like to see stable libraries at the moment they are not there."
"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."
"The solution should offer features for streaming data in addition to batching data."
"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 solution's visualization and analysis could be improved."
"The data lineage was challenging. It's hard to track data from the sources as it moves through stages. Informatica EDC can easily capture and report it because it talks to the metadata. This is generated across those various staging points."
"The workflow could be improved."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"Cost of this solution is quite high."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"Difficult to receive data from external sources."
"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."
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, Informatica Cloud Data Integration, SSIS and Denodo, whereas Palantir Foundry is most compared with Azure Data Factory, Palantir Gotham, SAP Data Services, Denodo and Mule Anypoint Platform. See our AWS Glue vs. Palantir Foundry report.
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