Google Cloud Managed Service for Apache Spark vs. Druid
A side-by-side comparison based on G2 review data.
| Metric | Google Cloud Managed Service for Apache Spark | Druid |
|---|---|---|
| Overall rating | 4.3 | 4.3 |
| Review count | 18 | 31 |
| Ease of use | 9.0 | 8.3 |
| Ease of setup | 7.1 | 6.9 |
| Quality of support | 9.0 | 8.2 |
| Meets requirements | 8.8 | 8.6 |
| NPS | 68.75 | 39.285714 |
| Small Business | 27.8% | 19.4% |
| Mid-Market | 38.9% | 29.0% |
| Enterprise | 33.3% | 51.6% |
| Total page views | 126 | 324 |
| Total LLM citations | 544 | 219 |
Google Cloud Managed Service for Apache Spark
Cloud Dataproc is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters in a simpler, more cost-efficient way. Operations that used to take hours or days take seconds or minutes instead, and you pay only for the resources you use (with per-second billing). Cloud Dataproc also easily integrates with other Google Cloud Platform (GCP) services, giving you a powerful and complete platform for data processing, analytics and machine learning.
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.