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."Data Factory's most valuable feature is Copy Activity."
"An excellent tool for pipeline orchestration."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"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."
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."
"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."
"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."
"The data lineage is great."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"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 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 virtualization tool is useful."
"The interface is really user-friendly."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"Snowflake connectivity was recently added and if the vendor provided some videos on how to create data then that would be helpful."
"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"Some known bugs and issues with Azure Data Factory could be rectified."
"The speed and performance need to be improved."
"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."
"The one element of the solution that we have used and could be improved is the user interface."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"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 solution could use more online documentation for new users."
"The workflow could be improved."
"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 would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"Difficult to receive data from external sources."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
Azure Data Factory is ranked 1st in Data Integration with 81 reviews while Palantir Foundry is ranked 11th in Data Integration with 13 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 Splunk Enterprise Security. See our Azure Data Factory vs. Palantir Foundry report.
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