Hive vs. Amazon Redshift
A side-by-side comparison based on G2 review data.
| Metric | Hive | Amazon Redshift |
|---|---|---|
| Overall rating | 4.2 | 4.3 |
| Review count | 60 | 404 |
| Ease of use | 8.6 | 8.9 |
| Ease of setup | 8.1 | 8.8 |
| Quality of support | 8.0 | 8.7 |
| Meets requirements | 8.5 | 8.9 |
| NPS | 43.859649 | 53.369272 |
| Small Business | 11.7% | 20.6% |
| Mid-Market | 35.0% | 39.3% |
| Enterprise | 53.3% | 40.0% |
| Total page views | 310 | 511 |
| Total LLM citations | 204 | 5,954 |
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.
Amazon Redshift
Tens of thousands of customers use Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It is optimized for datasets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
- Integrations
- Ease of Use
- Fast Querying
- Scalability
- Easy Integrations
- Performance