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."The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."
"When it comes to our business requirements, this solution has worked well for us. However, we have not stretched it to the limit."
"The best part of this product is the extraction, transformation, and load."
"Data Flow and Databricks are going to be extremely valuable services, allowing data solutions to scale as the business grows and new data sources are added."
"The scalability of the product is impressive."
"We haven't had any issues connecting it to other products."
"For developers that are very accustomed to the Microsoft development studio, it's very easy for them to complete end-to-end data integration."
"We have been using drivers to connect to various data sets and consume data."
"The solution offers very good end-to-end capabilities."
"Great features available in one tool."
"It's scalable."
"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 interface is really user-friendly."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"Data Factory's performance during heavy data processing isn't great."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"Data Factory has so many features that it can be a little difficult or confusing to find some settings and configurations. I'm sure there's a way to make it a little easier to navigate."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."
"The setup and configuration process could be simplified."
"It can improve from the perspective of active logging. It can provide active logging information."
"Difficult to receive data from external sources."
"Some error messages can be very cryptic."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"The solution's visualization and analysis could be improved."
"The solution could use more online documentation for new users."
"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."
"The workflow 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 Microsoft Azure Synapse Analytics, whereas Palantir Foundry is most compared with Palantir Gotham, SAP Data Services, AWS Glue, Denodo and Mule Anypoint Platform. See our Azure Data Factory vs. Palantir Foundry report.
See our list of best Data Integration vendors.
We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.