DVC vs. Databricks
A side-by-side comparison based on G2 review data.
| Metric | DVC | Databricks |
|---|---|---|
| Overall rating | 4.7 | 4.6 |
| Review count | 11 | 1,388 |
| Ease of use | 7.3 | 8.9 |
| Ease of setup | 7.1 | 8.7 |
| Quality of support | 7.7 | 8.9 |
| Meets requirements | 9.0 | 9.1 |
| NPS | 90.909091 | 77.851361 |
| Small Business | 27.3% | 15.1% |
| Mid-Market | 54.5% | 37.6% |
| Enterprise | 18.2% | 47.2% |
| Total page views | 64 | 16,340 |
| Total LLM citations | 165 | 14,031 |
DVC
DVC is an open-source, Git-based data science tool. Apply version control to machine learning development, make your repo the backbone of your project, and instill best practices across your team. Find more info at: https://dvc.org DVC has introduced a new open source tool for AI Data Analytics and Actionable GenAI Insights, that can curate vast amounts of unstructured data.
Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics, and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog.
- Features
- Ease of Use
- Integrations
- Collaboration
- Analytics
- Easy Integrations