Statements (56)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
software framework
|
| gptkbp:archives |
GitHub
|
| gptkbp:developedBy |
gptkb:Google
|
| gptkbp:firstPublished |
2016
|
| gptkbp:has |
Pipelines
I/O connectors Transforms Unified Model |
| gptkbp:hasFeature |
scalability
flexible resource management stateful processing watermarks integration with cloud services event time processing support for various data sinks support for various data sources batch and streaming unification cross-language support dataflow model dynamic work rebalancing support for machine learning windowing and triggers side inputs custom runners data-driven processing exactly-once processing monitoring and debugging tools multi-language SDKs rich set of connectors support for batch and streaming analytics support for graph processing fault_tolerance support_for_SQL_queries |
| gptkbp:hasOccupation |
gptkb:Apache_Software_Foundation
|
| gptkbp:hasVersion |
2.41.0
|
| https://www.w3.org/2000/01/rdf-schema#label |
BEAM
|
| gptkbp:isCompatibleWith |
gptkb:Apache_Beam_Runner
gptkb:Apache_Beam_SDK |
| gptkbp:isOpenTo |
true
|
| gptkbp:isUsedIn |
data analytics
data integration data processing |
| gptkbp:language |
gptkb:Java
Go Python Scala |
| gptkbp:provides |
stream processing
batch processing |
| gptkbp:supports |
stateful processing
event time processing windowing |
| gptkbp:uses |
gptkb:Apache_Flink
gptkb:Apache_Kafka gptkb:Apache_Spark Google Cloud Dataflow |
| gptkbp:website |
beam.apache.org
|