1. Data Sources: Dremio focuses on enabling querying and joining data across various formats and sources, including relational databases, NoSQL databases, and cloud storage services, providing a holistic view of the data landscape. On the other hand, Panoply primarily focuses on data integration and storage, consolidating data from different sources into a data warehouse for analytics, rather than joining data on the fly like Dremio.

2. Data Transformations: Dremio emphasizes on providing self-service data preparation capabilities, allowing users to transform and clean data within the platform before running queries. Additionally, Dremio supports in-place data transformations, eliminating the need to move data between locations. In contrast, Panoply focuses more on automating data transformation workflows, often requiring predefined transformations to be set up prior to analysis.

3. Scale and Performance: Dremio is designed for high-performance data processing, leveraging features like query acceleration, data reflection, and distributed query execution for optimized performance, especially with large datasets. Panoply, while offering scalable data storage, may not provide the same level of performance optimization for complex and resource-intensive queries.

4. Deployment Flexibility: Dremio can be deployed on-premises, in the cloud, or as a managed service, providing flexibility for organizations with different infrastructure requirements. On the contrary, Panoply typically offers a cloud-hosted solution, limiting deployment options for organizations that prefer on-premises infrastructure or have specific compliance needs.

5. Cost Model: Dremio's pricing model is based on a subscription fee, generally scaled according to the level of usage and required features, offering more flexibility for organizations with fluctuating data needs. In contrast, Panoply often follows a tiered pricing structure based on data volume and retention, which may lead to higher costs for organizations with unpredictable data growth or varying usage patterns.

6. Data Governance and Security: Dremio places a strong emphasis on data governance and security, providing features like role-based access control, data encryption, and audit logging to ensure data integrity and compliance with regulations. While Panoply also offers security features, the level of customization and control over data governance may not be as extensive as with Dremio.

In Summary, Dremio and Panoply differ in terms of data sources, data transformations, scale and performance, deployment flexibility, cost model, and data governance and security.