Spark Streaming vs. Hazelcast Platform
A side-by-side comparison based on G2 review data.
| Metric | Spark Streaming | Hazelcast Platform |
|---|---|---|
| Overall rating | 4.2 | 4.3 |
| Review count | 40 | 13 |
| Ease of use | 8.4 | 8.7 |
| Ease of setup | 7.9 | 8.3 |
| Quality of support | 8.8 | 8.9 |
| Meets requirements | 9.1 | 8.9 |
| NPS | 39.473684 | 41.666667 |
| Small Business | 30.8% | 53.8% |
| Mid-Market | 43.6% | 23.1% |
| Enterprise | 25.6% | 23.1% |
| Total page views | 74 | 83 |
| Total LLM citations | 66 | 138 |
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.
Hazelcast Platform
Hazelcast Platform is the Live Data Platform that delivers data at the speed of relevance, providing the in‑memory foundation for applications that act on data the instant it's created—ensuring businesses never miss a moment of opportunity. By converging distributed caching, compute, stream processing, and real‑time AI into one low‑latency runtime, Hazelcast delivers sub‑millisecond performance, linear scalability, and enterprise resilience. Global 2000 firms trust Hazelcast to simplify architectures, reduce costs, and power mission‑critical, time‑sensitive applications.
- Flexibility
- Ease of Use
- Performance Efficiency
- Performance
- Simple
- Fast Processing