

Find out in this report how the two Data Management Platforms (DMP) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
| Product | Market Share (%) |
|---|---|
| Palantir Foundry | 15.6% |
| Databricks | 2.3% |
| Other | 82.1% |

| Company Size | Count |
|---|---|
| Small Business | 25 |
| Midsize Enterprise | 12 |
| Large Enterprise | 56 |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 5 |
| Large Enterprise | 8 |
Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.
Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.
What features make Databricks unique?
What benefits can users expect from Databricks?
In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.
Palantir Foundry is an enterprise data management platform offering comprehensive tooling for working with big data. Because it is an operating system made for modern enterprises, it is highly available and a continuously updated platform.
Palantir Foundry is a fully managed SaaS platform that spans from cloud hosting and data integration to flexible analytics, visualization, model-building, operational decision-making, and decision capture. It equips technical and non-technical users to make data-driven operational decisions.
Palantir Foundry includes tools to integrate data of any scale, format, or structure, and also has granular, flexible access controls for individual datasets. In addition, it has an open, modular architecture with multiple RESTful APIs, it has native applications for developing machine learning and artificial intelligence, it provides sophisticated data science applications for users of all technical abilities, and much more.
Palantir Foundry Features
The most valuable Palantir Foundry features include:
Security, flexibility, interoperability, easy deployment, built-in role classification, purpose-based access controls, interoperable architecture, model integration, AI modeling tools, ontology, custom workflows, team-specific applications, self-serve analytics, lineage system, operational application building, 200+ data connectors, data versioning, change management framework, sand decision orchestration, and custom dashboard and report building tools.
With Palantir Foundry You Can:
Palantir Foundry Benefits
Some of the many Palantir Foundry benefits include:
Reviews from Real Users
PeerSpot users like Palantir Foundry because it has many advantages:
“It is user-friendly, good automation, and allows you to do a better job of data governance.” - Associate, Inhouse Consulting at a pharma/biotech company
“Works seamlessly with good end-to-end capabilities and the capability to scale.” - Wallace H., Sr. Director at a tech services company
We monitor all Data Management Platforms (DMP) 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.