Hive vs. Druid
A side-by-side comparison based on G2 review data.
| Metric | Hive | Druid |
|---|---|---|
| Overall rating | 4.2 | 4.3 |
| Review count | 60 | 31 |
| Ease of use | 8.6 | 8.3 |
| Ease of setup | 8.1 | 6.9 |
| Quality of support | 8.0 | 8.2 |
| Meets requirements | 8.5 | 8.6 |
| NPS | 43.859649 | 39.285714 |
| Small Business | 11.7% | 19.4% |
| Mid-Market | 35.0% | 29.0% |
| Enterprise | 53.3% | 51.6% |
| Total page views | 310 | 324 |
| Total LLM citations | 204 | 219 |
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.
Druid
Apache Druid is an open source real-time analytics database. Druid combines ideas from OLAP/analytic databases, timeseries databases, and search systems to create a complete real-time analytics solution for real-time data. It includes stream and batch ingestion, column-oriented storage, time-optimized partitioning, native OLAP and search indexing, SQL and REST support, flexible schemas; all with true horizontal scalability on a shared nothing, cloud native architecture that makes it easy to deploy, monitor and manage at scale.