Hive vs. Google Cloud BigQuery
A side-by-side comparison based on G2 review data.
| Metric | Hive | Google Cloud BigQuery |
|---|---|---|
| Overall rating | 4.2 | 4.5 |
| Review count | 60 | 1,223 |
| Ease of use | 8.6 | 8.9 |
| Ease of setup | 8.1 | 8.9 |
| Quality of support | 8.0 | 8.6 |
| Meets requirements | 8.5 | 9.0 |
| NPS | 43.859649 | 67.744755 |
| Small Business | 11.7% | 27.7% |
| Mid-Market | 35.0% | 34.3% |
| Enterprise | 53.3% | 38.1% |
| Total page views | 310 | 5,950 |
| Total LLM citations | 204 | 27,007 |
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.
Google Cloud BigQuery
BigQuery is an AI-ready, petabyte-scale, and cost-effective data warehouse that lets you run analytics over vast amounts of data in near real time. Store 10 GiB of data and run up to 1 TiB of queries for free per month.
- Ease of Use
- Speed
- Integrations
- Fast Querying
- Query Efficiency
- Scalability