Spark Streaming vs. Amazon Kinesis Data Streams
A side-by-side comparison based on G2 review data.
| Metric | Spark Streaming | Amazon Kinesis Data Streams |
|---|---|---|
| Overall rating | 4.2 | 4.3 |
| Review count | 40 | 90 |
| Ease of use | 8.4 | 8.6 |
| Ease of setup | 7.9 | 8.8 |
| Quality of support | 8.8 | 8.8 |
| Meets requirements | 9.1 | 9.2 |
| NPS | 39.473684 | 49.382716 |
| Small Business | 30.8% | 26.7% |
| Mid-Market | 43.6% | 36.7% |
| Enterprise | 25.6% | 36.7% |
| Total page views | 74 | 137 |
| Total LLM citations | 66 | 670 |
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 Streams
Amazon Kinesis Data Streams is a massively scalable, durable, and low-cost streaming data service. Kinesis Data Streams can continuously capture gigabytes of data per second from hundreds of thousands of sources, such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs, and location-tracking events. The collected data is available in milliseconds to allow real-time analytics use cases, such as real-time dashboards, real-time anomaly detection, dynamic pricing.
- Real-Time Processing
- Streaming
- Real-time Data
- Real-time Streaming
- Real-time Processing
- Time Management