Azure Data Factory vs. dbt
A side-by-side comparison based on G2 review data.
| Metric | Azure Data Factory | dbt |
|---|---|---|
| Overall rating | 4.6 | 4.7 |
| Review count | 102 | 209 |
| Ease of use | 9.1 | 9.1 |
| Ease of setup | 9.2 | 8.8 |
| Quality of support | 9.0 | 9.0 |
| Meets requirements | 9.3 | 9.3 |
| NPS | 76.28866 | 81.25 |
| Small Business | 11.9% | 27.1% |
| Mid-Market | 28.7% | 56.5% |
| Enterprise | 59.4% | 16.4% |
| Total page views | 445 | 780 |
| Total LLM citations | 1,119 | 4,329 |
Azure Data Factory
Azure Data Factory (ADF) is a fully managed, serverless data integration service designed to simplify the process of ingesting, preparing, and transforming data from diverse sources. It enables organizations to construct and orchestrate Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) workflows in a code-free environment, facilitating seamless data movement and transformation across on-premises and cloud-based systems.
- Data Integration
- Ease of Use
- Integrations
- Scalability
- Connectors
- Simple
dbt
dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines.
- Ease of Use
- Features
- Automation
- Transformation
- Productivity Improvement
- Data Quality