1. Deployment Requirements: Dremio can be deployed on-premise, in the cloud, or as a managed service, providing flexibility in deployment options. In contrast, Kylo is designed for on-premise deployment only, limiting its deployment options for organizations looking for cloud-based solutions.
2. User Interface: Dremio offers a sleek and intuitive user interface that simplifies data exploration and query execution for users. On the other hand, Kylo's user interface is more focused on data ingestion and preparation, with less emphasis on data exploration capabilities.
3. Data Integration: Dremio provides advanced data integration capabilities, allowing users to easily connect and query multiple data sources without the need for complex configurations. In comparison, Kylo puts more emphasis on data ingestion workflows and does not offer the same level of flexibility for data integration.
4. Data Governance: Dremio offers robust data governance features, including fine-grained access controls and auditing capabilities, to ensure data security and compliance. Kylo lacks the same level of data governance functionality, making it less suitable for organizations with strict regulatory requirements.
5. Scalability: Dremio is highly scalable and can efficiently handle large volumes of data processing and analytical workloads. Kylo, while scalable to some extent, may face limitations in handling extremely large-scale data processing tasks, which can impact performance and user experience.
6. Community Support: Dremio has a strong and active community of users and contributors, providing access to resources, documentation, and support forums. Kylo, on the other hand, has a smaller community and may have limited community-driven support resources available.

In Summary, Dremio offers greater deployment flexibility, a more user-friendly interface, advanced data integration capabilities, robust data governance features, scalability, and a stronger community support compared to Kylo.