Azure Data Factory vs. IBM StreamSets
A side-by-side comparison based on G2 review data.
| Metric | Azure Data Factory | IBM StreamSets |
|---|---|---|
| Overall rating | 4.6 | 4.0 |
| Review count | 102 | 115 |
| Ease of use | 9.1 | 8.6 |
| Ease of setup | 9.2 | 8.3 |
| Quality of support | 9.0 | 8.3 |
| Meets requirements | 9.3 | 8.4 |
| NPS | 76.28866 | 29.20354 |
| Small Business | 11.9% | 23.7% |
| Mid-Market | 28.7% | 33.3% |
| Enterprise | 59.4% | 43.0% |
| Total page views | 445 | 297 |
| Total LLM citations | 1,119 | 1,104 |
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
IBM StreamSets
IBM StreamSets is a robust streaming data integration tool for hybrid, multi-cloud environments that enables real-time decision making. It allows ingestion and in-flight transformation of structured, unstructured, and semi-structured data from streaming sources, and reliably delivers trusted data into diverse destinations. Flexible deployment options promote security, cost-effectiveness and performance. With several pre-built connectors, an intuitive no-code/low-code interface, and automatic adaptability to data drifts, StreamSets accelerates data pipeline operationalization.
- Ease of Use
- User Interface
- Data Pipelining
- Data Management
- Integrations
- Implementation Ease