Google Cloud BigQuery vs. Druid
A side-by-side comparison based on G2 review data.
| Metric | Google Cloud BigQuery | Druid |
|---|---|---|
| Overall rating | 4.5 | 4.3 |
| Review count | 1,223 | 31 |
| Ease of use | 8.9 | 8.3 |
| Ease of setup | 8.9 | 6.9 |
| Quality of support | 8.6 | 8.2 |
| Meets requirements | 9.0 | 8.6 |
| NPS | 67.744755 | 39.285714 |
| Small Business | 27.7% | 19.4% |
| Mid-Market | 34.3% | 29.0% |
| Enterprise | 38.1% | 51.6% |
| Total page views | 5,950 | 324 |
| Total LLM citations | 27,007 | 219 |
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
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.