

Alteryx and Palantir Foundry compete in the data preparation and analytics space. Alteryx is preferred for ease of use with its drag-and-drop tools, while Palantir Foundry's strength lies in its scalability and integration capabilities, making it advantageous for enterprise solutions.
Features: Alteryx offers user-friendly drag-and-drop functionality, intuitive workflow tools, and robust data connectivity, providing non-technical users the ability to perform complex data manipulations easily. Palantir Foundry excels with its scalable architecture, comprehensive data model management with Ontology, and powerful AI-driven analysis features, supporting complex enterprise data environments.
Room for Improvement: Alteryx users cite high costs and limited advanced analytics as areas to improve, also seeking expanded cloud options and connectors. Palantir Foundry, while comprehensive, is critiqued for its steep learning curve, high setup costs, and the need for better user-interaction improvements and documentation clarity.
Ease of Deployment and Customer Service: Alteryx provides flexible deployment options like on-premise and private cloud, alongside reliable customer support and an active user community. Palantir Foundry focuses on cloud deployment, which can be complex but is supported by robust service offerings, ensuring stability and assistance during challenging setups.
Pricing and ROI: Alteryx's premium pricing suits larger enterprises, offering significant ROI through process automation. Palantir Foundry, although involving a high initial investment, promises better cost efficiency over time due to reduced development efforts and supports large-scale organizations achieving strategic ROI benefits in data management.
Tasks that earlier took hours in Excel or SQL are now completed in minutes.
From a time-saving perspective, we saved 60 to 75 percent of the human workforce needed and eliminated other disparate ETL tools, ultimately saving us over 600,000 dollars.
Alteryx helps familiarize managers with artificial intelligence-driven possibilities.
With traditional development requiring many specialized roles, Palantir Foundry allows us to operate efficiently with fewer personnel.
We saved approximately 20 to 35 percent in man-hours needed and the timing improved our project timelines by approximately 50 to 55 percent.
One clear example was the pipeline optimization I mentioned, where we reduced execution time by thirty to forty percent.
Customer support from Alteryx has been amazing.
they do have a website for resolving doubts and accessing helpful resources, including various tools and filters.
I contacted customer support once or twice, and they were quick to respond.
They are knowledgeable, and their boot camps demonstrate solutions in just three days, which typically takes months or years.
When I seek help regarding code in Slate, it can take considerable time for the team to find the right answer or documentation, especially since the responses depend on the level of support provided, and specific queries regarding coding usually require reaching out to more experienced developers.
The support staff are extremely knowledgeable and good at what they are doing.
Alteryx is scalable for most enterprise analytics and data preparation workloads.
Suggestions for improvements in Alteryx include areas for increasing efficiency, particularly in processing telemetry data, which involves dealing with large volumes of unstructured data.
Alteryx is scalable, and I would give it eight out of ten.
We work with large volumes of healthcare data, and it has been able to handle all the large-scale ingestion, transformation, and distributed processing workflows effectively.
For scalability, I would rate it ten out of ten because you have a lot of flexibility.
Regarding scalability, if you have billions and trillions of records, Palantir Foundry accommodates ETL pipelines with a dedicated compute profile.
I didn't need to reach out to Alteryx for support because available documents usually provide enough information to resolve issues.
I have not encountered any lagging, crashing, or instability in the system during these three months of usage.
Alteryx is a reliable tool, but it is also very heavy, requiring good laptop configurations, a minimum of 8GB RAM, and a recent processor such as i10.
Live data streaming is very hard and it keeps breaking, so it is not very stable and depends a lot on the satellite network.
I get more technical support from Palantir.
Palantir Foundry has been a stable and reliable enterprise platform.
The tool could include more native connectors, such as for global ERPs, instead of requiring additional fees for these connections.
The support structure changed; initially, we received great support, however, it later became less reliable due to licensing issues and a tiered support system.
The additional features that Alteryx needs to work on to make it more competitive include better collaboration and easier integration through API.
The platform is extremely capable, but improvements around usability, debugging experience, DevOps flexibility, and ecosystem openness would make it even more effective for enterprise engineering teams.
I want to build conversational BI or conversational agents quickly that can connect to MCPs, and other MCPs that I can communicate with in Palantir Foundry, which are areas to advance forward.
An improvement would be that in case of any changes done by the Palantir team, those changes need to be tested thoroughly so there are no downstream impacts, ensuring that the business is not affected by any modifications in the system.
The price is very high, with licensing typically starting around five thousand dollars plus user per year.
We found excellent use cases for automation through Alteryx, which provided the means to reduce operational costs and streamline the build of ETL pipelines without extensive coding.
Alteryx is more cost-effective compared to Informatica licenses, offering savings.
Its high initial pricing can be intimidating, but it becomes cost-effective as it reduces the need for a development team.
In terms of getting a contractor to work on that, I would probably say it is more expensive because there are fewer people with that skillset compared to, say, Databricks or Azure.
We can consult it in the right way regarding Palantir Foundry use, as it is still a gray area right now concerning costing.
Alteryx not only represents data but also supports decision-making by suggesting the next steps.
Analysts who do not have any coding experience can still work on the transformation and preparation of data, which is quite useful.
Alteryx includes built-in tools such as drive time analysis and linear regression, which are much harder to achieve in standard BI tools such as Power BI or Tableau.
The predictive analytics capability within Palantir Foundry impacts financial forecasting strategies through its AIP functionality, which includes numerous pre-built models, LLMs, and data science application libraries.
The main advantage is you can decentralize the analytics, and you will have everything in one place, so that you do not need to rely on multiple departments working on different tools.
The low-code solutions made our lives easier because not everybody is too technical to get started and the barrier to entry is very low.
| Product | Mindshare (%) |
|---|---|
| Palantir Foundry | 2.2% |
| Alteryx | 1.2% |
| Other | 96.6% |

| Company Size | Count |
|---|---|
| Small Business | 46 |
| Midsize Enterprise | 20 |
| Large Enterprise | 73 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 7 |
| Large Enterprise | 51 |
Alteryx enhances efficiency by automating data preparation and transformation through a user-friendly drag-and-drop interface, catering to non-technical users and business professionals. It supports data blending, predictive analytics, and diverse data integration capabilities.
Alteryx streamlines data manipulation and complex transformations, benefiting industries such as finance and marketing with its ability to connect to multiple data sources and automate workflows. The platform supports analytics and machine learning model building, reducing manual efforts in ETL processes. Despite its capabilities, improvements are needed in database connectivity, pricing flexibility, and cloud service integration. Users desire enhancements in reporting features, visualization, and technical support to optimize its full potential. Machine learning and predictive analytics features require advancements to improve user experience and broaden accessibility through better connectors and reduced licensing costs.
What are Alteryx's key features?
What benefits and ROI should be looked for in reviews?
In finance and marketing, organizations leverage Alteryx to automate data tasks, connect diverse sources, and generate analytics models and dashboards efficiently. Its no-code approach aids in rapid data preparation, cleansing, and analysis, empowering business users to engage in predictive and prescriptive analytics effectively.
Palantir Foundry offers intuitive data management and application development, prioritizing accessibility through low-code/no-code tools, enabling users to integrate, analyze, and collaborate efficiently.
Palantir Foundry centers on user accessibility, data governance, and real-time capabilities, streamlining processes with low-code/no-code development. It supports comprehensive data analysis and integration, enhanced by digital twin features that align virtual and physical interactions. Despite high costs and performance challenges with large datasets, it remains a prime choice for sectors needing structured and unstructured data integration. Key areas include robust data security, lineage tracking, and predictive analytics, promoted through a unified management platform adaptable to diverse needs.
What are the key features of Palantir Foundry?In manufacturing, Palantir Foundry aids in engineering pipeline models and semantic frameworks, while utilities utilize its analytics to enhance service delivery. Insurance firms leverage its capability to assess and predict customer behavior. Throughout these industries, Foundry integrates across cloud environments, bridging structured and unstructured data from various sources.
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