Spark Streaming vs. Red Hat OpenShift Streams for Apache Kafka
A side-by-side comparison based on G2 review data.
| Metric | Spark Streaming | Red Hat OpenShift Streams for Apache Kafka |
|---|---|---|
| Overall rating | 4.2 | 4.4 |
| Review count | 40 | 26 |
| Ease of use | 8.4 | 8.6 |
| Ease of setup | 7.9 | 8.7 |
| Quality of support | 8.8 | 9.1 |
| Meets requirements | 9.1 | 8.8 |
| NPS | 39.473684 | 53.846154 |
| Small Business | 30.8% | 42.3% |
| Mid-Market | 43.6% | 19.2% |
| Enterprise | 25.6% | 38.5% |
| Total page views | 74 | 66 |
| Total LLM citations | 66 | 141 |
Spark Streaming
Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part.
Red Hat OpenShift Streams for Apache Kafka
Red Hat® OpenShift® Streams for Apache Kafka is a managed cloud service that provides a streamlined developer experience for building, deploying, and scaling new cloud-native applications or modernizing existing systems.