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 feature of Azure Data Factory is that it has a good combination of flexibility, fine-tuning, automation, and good monitoring."
"The workflow automation features in GitLab, particularly its low code/no code approach, are highly beneficial for accelerating development speed. This feature allows for quick creation of pipelines and offers customization options for integration needs, making it versatile for various use cases. GitLab supports a wide range of connectors, catering to a majority of integration needs. Azure Data Factory's virtual enterprise and monitoring capabilities, the visual interface of GitLab makes it user-friendly and easy to teach, facilitating adoption within teams. While the monitoring capabilities are sufficient out of the box, they may not be as comprehensive as dedicated enterprise monitoring tools. GitLab's monitoring features are manageable for production use, with the option to integrate log analytics or create custom dashboards if needed. The data flow feature in Azure Data Factory within GitLab is valuable for data transformation tasks, especially for those who may not have expertise in writing complex code. It simplifies the process of data manipulation and is particularly useful for individuals unfamiliar with Spark coding. While there could be improvements for more flexibility, overall, the data flow feature effectively accomplishes its purpose within GitLab's ecosystem."
"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"The scalability of the product is impressive."
"The most valuable aspect is the copy capability."
"I like how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."
"From what we have seen so far, the solution seems very stable."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"The solution offers very good end-to-end capabilities."
"It's scalable."
"Great features available in one tool."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"The data lineage is great."
"The interface is really user-friendly."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"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."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"Data Factory's performance during heavy data processing isn't great."
"The product could provide more ways to import and export data."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"When the record fails, it's tough to identify and log."
"There's space for improvement in the development process of the data pipelines."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"The frontend capabilities of Palantir Foundry could be improved."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"Cost of this solution is quite high."
"Some error messages can be very cryptic."
"The solution's visualization and analysis could be improved."
"Difficult to receive data from external sources."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"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.
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