Azure Databricks vs. Dataiku
A side-by-side comparison based on G2 review data.
| Metric | Azure Databricks | Dataiku |
|---|---|---|
| Overall rating | 4.5 | 4.4 |
| Review count | 240 | 267 |
| Ease of use | 8.9 | 8.8 |
| Ease of setup | 8.9 | 8.4 |
| Quality of support | 8.7 | 8.7 |
| Meets requirements | 9.0 | 8.9 |
| NPS | 68.691589 | 58.267717 |
| Small Business | 25.1% | 18.6% |
| Mid-Market | 27.6% | 22.4% |
| Enterprise | 47.3% | 58.9% |
| Total page views | 404 | 1,763 |
| Total LLM citations | 1,981 | 16,600 |
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
Dataiku
Dataiku is the Platform for AI Success: the AI orchestration layer where enterprises build, deploy, and govern analytics, models, and agents at scale. It sits on top of the data platforms, clouds, and AI services you already use, working across all of them without locking you into any one. Dataiku expands who can build production AI, putting the right tools in the hands of data scientists and domain experts alike, from fraud analysts to demand planners. It orchestrates machine learning, rules, LLMs, and agents as one governed system, built on more than a decade of running production AI.
- Features
- Ease of Use
- Usability
- Easy Integrations
- Productivity Improvement
- Collaboration