We performed a comparison between Azure Data Factory and Palantir Foundry based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."We have been using drivers to connect to various data sets and consume data."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"The user interface is very good. It makes me feel very comfortable when I am using the tool."
"The overall performance is quite good."
"This solution will allow the organisation to improve its existing data offerings over time by adding predictive analytics, data sharing via APIs and other enhancements readily."
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"It is beneficial that the solution is written with Spark as the back end."
"The most valuable feature is the copy activity."
"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 data lineage is great."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"The AI engine that comes with Palantir Foundry is quite interesting."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"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."
"The virtualization tool is useful."
"Currently, smaller businesses face a disadvantage in terms of pricing, and reducing costs could address this issue."
"It would be better if it had machine learning capabilities."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"The Microsoft documentation is too complicated."
"Difficult to receive data from external sources."
"Some error messages can be very cryptic."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"The solution could use more online documentation for new users."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"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."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"The frontend capabilities of Palantir Foundry could be improved."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Palantir Foundry is ranked 11th in Data Integration with 14 reviews. Azure Data Factory is rated 8.0, while Palantir Foundry is rated 7.6. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". On the other hand, the top reviewer of Palantir Foundry writes "The data visualization is fantastic and the security is excellent". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Oracle Data Integrator (ODI), whereas Palantir Foundry is most compared with Palantir Gotham, SAP Data Services, AWS Glue, Alteryx Designer and Denodo. See our Azure Data Factory vs. Palantir Foundry report.
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