Neo4j Graph Data Science vs. Spearmint
A side-by-side comparison based on G2 review data.
| Metric | Neo4j Graph Data Science | Spearmint |
|---|---|---|
| Overall rating | 4.5 | 4.4 |
| Review count | 16 | 14 |
| Ease of use | 8.7 | 9.5 |
| Ease of setup | 8.2 | 9.6 |
| Quality of support | 9.0 | 9.0 |
| Meets requirements | 9.1 | 9.0 |
| NPS | 73.333333 | 78.571429 |
| Small Business | 37.5% | 28.6% |
| Mid-Market | 43.8% | 50.0% |
| Enterprise | 18.8% | 21.4% |
| Total page views | 90 | 17 |
| Total LLM citations | 557 | 13 |
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
Spearmint
Spearmint is a software package to perform Bayesian optimization that automatically run experiments (thus the code name spearmint) in a manner that iteratively adjusts a number of parameters so as to minimize some objective in as few runs as possible.