Spark Streaming vs. Amazon Kinesis Data Analytics
A side-by-side comparison based on G2 review data.
| Metric | Spark Streaming | Amazon Kinesis Data Analytics |
|---|---|---|
| Overall rating | 4.2 | 4.1 |
| Review count | 40 | 15 |
| Ease of use | 8.4 | 8.6 |
| Ease of setup | 7.9 | 8.0 |
| Quality of support | 8.8 | 8.1 |
| Meets requirements | 9.1 | 8.0 |
| NPS | 39.473684 | 42.857143 |
| Small Business | 30.8% | 26.7% |
| Mid-Market | 43.6% | 6.7% |
| Enterprise | 25.6% | 66.7% |
| Total page views | 74 | 27 |
| Total LLM citations | 66 | 13 |
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.
Amazon Kinesis Data Analytics
Amazon Kinesis Data Analytics is the easiest way to transform and analyze streaming data in real time with Apache Flink. Kinesis Data Analytics reduces the complexity of building, managing, and integrating Apache Flink applications with other AWS services. Kinesis Data Analytics takes care of everything required to run streaming applications continuously, and scales automatically to match the volume and throughput of your incoming data.
- Integrations
- Analytics
- Security Protection
- Cost Saving
- Easy Integrations
- Cloud Services