Cloudera Enterprise vs Dremio: What are the differences?

<Setting the stage: Cloudera Enterprise and Dremio are both data management platforms used in enterprises. Cloudera Enterprise primarily focuses on Hadoop and Big Data analytics, whereas Dremio provides a Data-as-a-Service platform for self-service data analytics.>

1. Architecture: Cloudera Enterprise follows a traditional distributed computing architecture, with Hadoop as the core technology stack, while Dremio uses a unique Data Reflections technology to accelerate query performance by caching and pre-materializing data.

2. Data Virtualization: Dremio offers data virtualization capabilities, allowing users to access and query data from multiple sources without physically moving it, while Cloudera Enterprise focuses more on storing and processing structured and unstructured data on Hadoop clusters.

3. Self-Service Analytics: Dremio is designed for self-service data analytics, enabling business users to explore and visualize data without the need for IT intervention, while Cloudera Enterprise requires more technical expertise for data processing and analytics tasks.

4. Cost Model: Cloudera Enterprise follows a subscription-based pricing model that includes support and services, while Dremio offers a consumption-based pricing model where users pay for the resources they use, making it more cost-effective for smaller workloads.

5. Data Governance: Cloudera Enterprise provides robust data governance capabilities for managing and securing data across the organization, while Dremio focuses more on enhancing data accessibility and query performance, with limited governance features.

6. Community Support: Dremio has a strong open-source community backing it, enabling users to contribute to the platform's development and engage in discussions, while Cloudera Enterprise relies more on its enterprise customer base for feedback and support.

In Summary, Cloudera Enterprise focuses on traditional big data processing with Hadoop, while Dremio offers a modern approach with self-service data analytics and data virtualization capabilities.