Google Cloud Managed Service for Apache Spark vs. Google Cloud Dataflow
A side-by-side comparison based on G2 review data.
| Metric | Google Cloud Managed Service for Apache Spark | Google Cloud Dataflow |
|---|---|---|
| Overall rating | 4.3 | 4.2 |
| Review count | 18 | 44 |
| Ease of use | 9.0 | 8.3 |
| Ease of setup | 7.1 | 8.2 |
| Quality of support | 9.0 | 8.6 |
| Meets requirements | 8.8 | 9.1 |
| NPS | 68.75 | 42.857143 |
| Small Business | 27.8% | 36.4% |
| Mid-Market | 38.9% | 31.8% |
| Enterprise | 33.3% | 31.8% |
| Total page views | 126 | 219 |
| Total LLM citations | 544 | 272 |
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.
Google Cloud Dataflow
Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed. And with its serverless approach to resource provisioning and management, you have access to virtually limitless capacity to solve your biggest data processing challenges, while paying only for what you use.
- Features
- Real-time Analytics
- Insights
- Real-Time Processing
- Easy Management
- Speed