Hive vs. Starburst
A side-by-side comparison based on G2 review data.
| Metric | Hive | Starburst |
|---|---|---|
| Overall rating | 4.2 | 4.3 |
| Review count | 60 | 127 |
| Ease of use | 8.6 | 8.9 |
| Ease of setup | 8.1 | 8.6 |
| Quality of support | 8.0 | 9.0 |
| Meets requirements | 8.5 | 9.0 |
| NPS | 43.859649 | 51.587302 |
| Small Business | 11.7% | 38.6% |
| Mid-Market | 35.0% | 23.6% |
| Enterprise | 53.3% | 37.8% |
| Total page views | 310 | 853 |
| Total LLM citations | 204 | 4,628 |
Hive
Hive provides a mechanism to project structure onto this data and query the data using a SQL-like language called HiveQL. At the same time this language also allows traditional map/reduce programmers to plug in their custom mappers and reducers when it is inconvenient or inefficient to express this logic in HiveQL.
Starburst
Starburst is the data platform for analytics, applications, and AI, unifying data across clouds and on-premises to accelerate AI innovation. Organizations—from startups to Fortune 500 enterprises in 60+ countries—rely on Starburst for fast data access, seamless collaboration, and enterprise-grade governance on an open hybrid data lakehouse. Wherever data lives, Starburst unlocks its full potential, powering data and AI from development to deployment. By future-proofing data architecture, Starburst helps businesses fuel innovation with AI. Learn more at starburst.ai
- Fast Querying
- Query Efficiency
- Integrations
- Ease of Use
- Large Datasets
- Performance