

Palantir Foundry and CloudQuery compete in the data processing tools category. Despite Palantir Foundry's favorable support and pricing structure, CloudQuery has the upper hand with its open-source model offering superior flexibility and customization.
Features: Palantir Foundry offers robust data integration, comprehensive analytics capabilities, and scalability in complex environments. CloudQuery provides specialized cloud infrastructure data querying, extensive custom modification options, and a flexible approach due to its open-source nature.
Ease of Deployment and Customer Service: Palantir Foundry requires significant initial setup but provides strong support channels for smoother post-deployment operations. CloudQuery’s straightforward deployment benefits from its open-source framework, but it may lack formal support channels, offering improved adaptability.
Pricing and ROI: Palantir Foundry requires a higher initial investment in line with its full-scale integration and valuable analytics, potentially providing substantial ROI for large-scale projects. CloudQuery's open-source nature offers lower-cost entry, appealing to organizations focusing on cost-effectiveness with adaptable data solutions.
I could find the same asset information in CloudQuery in less than an hour, whereas Prisma took hours and hours to get things figured out.
This enables me to manage cloud infrastructure efficiently, avoiding multiple investments in different data management and cloud infrastructure monitoring systems.
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.
They took my feedback and implemented things very quickly.
Customer support is attentive and willing to listen to clients, providing accurate information upon queries and guiding users in a clear and understandable manner.
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.
The scalability plan for CloudQuery is well executed; as we continue to grow and require additional packages, the vendor supports me well, and the scalability process is straightforward with minimal hindrances.
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.
CloudQuery is stable and provides consistent services with no downtime, allowing my organization to receive services effectively.
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.
CloudQuery's AI capabilities lack governance and security features.
Regarding CloudQuery's AI capabilities and its accuracy and reliability of output, it is very good because it transforms all your SQL and gives you some advice about what to do.
It is not a platform suitable for layman staff or those lacking proficiency; it demands knowledge in data integration, cloud infrastructure, and SQL.
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.
My experience with pricing, setup costs, and licensing was not frustrating; I executed everything smoothly by following the vendor's outlined steps, resulting in a rewarding experience.
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.
I was spending hours trying to craft an RQL for Prisma, but I could figure out the SQL in CloudQuery in minutes.
It helps close compliance and security gaps; with that view, I can generate reports highlighting vulnerabilities, leading me to plan better and eliminate any exposures, thus ensuring effective execution of my work.
The best features CloudQuery offers include some FinOps tools to help you analyze unused or underutilized resources.
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 | 3.9% |
| CloudQuery | 0.7% |
| Other | 95.4% |

| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 2 |
| Large Enterprise | 3 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 7 |
| Large Enterprise | 51 |
CloudQuery enables users to transform cloud infrastructure into SQL databases for streamlined data analysis and security assessments. Tailored for those who require efficient cloud configuration and security management capabilities, it functions seamlessly across diverse platforms.
Designed to convert cloud infrastructure data into SQL, CloudQuery leverages open-source technology for extensive customization. It offers immediate insights through powerful data querying, supporting comprehensive audits and compliance checks. Its flexibility and scalability make it ideal for advanced data management and security scrutiny.
What key features does CloudQuery offer?CloudQuery's implementation varies, becoming an integral part of financial institutions for ensuring compliance, while technology firms utilize its querying capabilities to optimize cloud data management and security. In healthcare, it supports data privacy and integrity through robust configuration management.
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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