Azure Databricks vs. Dremio
A side-by-side comparison based on G2 review data.
| Metric | Azure Databricks | Dremio |
|---|---|---|
| Overall rating | 4.5 | 4.6 |
| Review count | 240 | 71 |
| Ease of use | 8.9 | 9.3 |
| Ease of setup | 8.9 | 8.7 |
| Quality of support | 8.7 | 8.8 |
| Meets requirements | 9.0 | 8.9 |
| NPS | 68.691589 | 76.923077 |
| Small Business | 25.1% | 11.3% |
| Mid-Market | 27.6% | 39.4% |
| Enterprise | 47.3% | 49.3% |
| Total page views | 404 | 429 |
| Total LLM citations | 1,981 | 2,089 |
Azure Databricks
Azure Databricks is a unified, open analytics platform developed collaboratively by Microsoft and Databricks. Built on the lakehouse architecture, it seamlessly integrates data engineering, data science, and machine learning within the Azure ecosystem. This platform simplifies the development and deployment of data-driven applications by providing a collaborative workspace that supports multiple programming languages, including SQL, Python, R, and Scala.
- Ease of Use
- Features
- Integrations
- Speed
- Scaling
- Analytics
Dremio
Dremio is the pioneer of The Agentic Lakehouse—the only data platform built for agents, managed by agents. Organizations need to transform ideas into actions at unprecedented speed—Dremio delivers this agility by equipping AI agents with federated data access, unstructured data processing, and rich business context through its AI Semantic Layer. In the agentic-era, data engineering teams can’t manually tune performance for thousands of users and agents asking unpredictable questions every second.
- Ease of Use
- Integrations
- SQL Support
- Performance
- Setup Ease
- Speed