How do refinements relate?
| Google Cloud Dataflow | Prism Local Runner | Apache Flink | Apache Spark (RDD/DStream based) | Apache Spark Structured Streaming (Dataset based) | Apache Nemo | Hazelcast Jet | Kafka Streams (experimental, not released) | Twister2 | Python Direct FnRunner | |
|---|---|---|---|---|---|---|---|---|---|---|
| Discarding | Yes : fully supported | Yes : fully supported | Yes : fully supported | Yes : fully supported Spark streaming natively discards elements after firing. | Partially : fully supported in batch mode | Yes : fully supported | Yes : fully supported | Yes : fully supported | Yes : fully supported | Yes : fully supported |
| Accumulating | Yes : fully supported Requires that the accumulated pane fits in memory, after being passed through the combiner (if relevant) | Yes : fully supported | Yes : fully supported | No | No | Yes : fully supported | Yes : fully supported | Yes : fully supported | Yes : fully supported | Yes : fully supported |
Last updated on 2026/08/28
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