Azure Machine Learning vs. Dataiku
A side-by-side comparison based on G2 review data.
| Metric | Azure Machine Learning | Dataiku |
|---|---|---|
| Overall rating | 4.3 | 4.4 |
| Review count | 90 | 267 |
| Ease of use | 8.7 | 8.8 |
| Ease of setup | 8.6 | 8.4 |
| Quality of support | 8.8 | 8.7 |
| Meets requirements | 8.7 | 8.9 |
| NPS | 48.275862 | 58.267717 |
| Small Business | 33.3% | 18.6% |
| Mid-Market | 26.7% | 22.4% |
| Enterprise | 40.0% | 58.9% |
| Total page views | 239 | 1,763 |
| Total LLM citations | 1,035 | 16,600 |
Azure Machine Learning
Azure Machine Learning is an enterprise-grade service that facilitates the end-to-end machine learning lifecycle, enabling data scientists and developers to build, train, and deploy models efficiently. Key Features and Functionality: - Data Preparation: Quickly iterate data preparation on Apache Spark clusters within Azure Machine Learning, interoperable with Microsoft Fabric. - Feature Store: Increase agility in shipping your models by making features discoverable and reusable across workspaces.
- Features
- Ease of Use
- Customer Support
- Data Management
- Implementation Ease
- Efficiency
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