Neo4j Graph Data Science vs. Dataiku
A side-by-side comparison based on G2 review data.
| Metric | Neo4j Graph Data Science | Dataiku |
|---|---|---|
| Overall rating | 4.5 | 4.4 |
| Review count | 16 | 267 |
| Ease of use | 8.7 | 8.8 |
| Ease of setup | 8.2 | 8.4 |
| Quality of support | 9.0 | 8.7 |
| Meets requirements | 9.1 | 8.9 |
| NPS | 73.333333 | 58.267717 |
| Small Business | 37.5% | 18.6% |
| Mid-Market | 43.8% | 22.4% |
| Enterprise | 18.8% | 58.9% |
| Total page views | 90 | 1,763 |
| Total LLM citations | 557 | 16,600 |
Neo4j Graph Data Science
Neo4j Graph Data Science is a data science and machine learning engine that uses the relationships in your data to improve predictions. It plugs into enterprise data ecosystems so you can get more data science projects into production quickly. Using a catalog of over 65 pretuned graph algorithms, data scientists can explore billions of data points in seconds to identify hidden connections and generate compelling visualizations that lead to better stakeholder decision making.
- Ease of Use
- Model Variety
- Problem Solving
- Machine Learning
- Scalability
- 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