Kafka Streams
E702192
Kafka Streams is a Java library for building real-time, distributed stream processing applications on top of Apache Kafka.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Kafka Streams canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T7985614 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kafka Streams Context triple: [Apache Storm, competesWith, Kafka Streams]
-
A.
Apache Kafka
Apache Kafka is a distributed event streaming platform widely used for building real-time data pipelines and streaming applications.
-
B.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
-
C.
KSQL
KSQL is the ICAO airport code for San Carlos Airport, a general aviation facility serving the San Francisco Bay Area in California.
-
D.
IBM Streams
IBM Streams is a high-performance stream processing platform that enables real-time ingestion, analysis, and correlation of large-scale data in motion for enterprise applications.
-
E.
Apache Storm
Apache Storm is a distributed real-time computation system designed for processing large streams of data with low latency and high fault tolerance.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kafka Streams Target entity description: Kafka Streams is a Java library for building real-time, distributed stream processing applications on top of Apache Kafka.
-
A.
Apache Kafka
Apache Kafka is a distributed event streaming platform widely used for building real-time data pipelines and streaming applications.
-
B.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
-
C.
KSQL
KSQL is the ICAO airport code for San Carlos Airport, a general aviation facility serving the San Francisco Bay Area in California.
-
D.
IBM Streams
IBM Streams is a high-performance stream processing platform that enables real-time ingestion, analysis, and correlation of large-scale data in motion for enterprise applications.
-
E.
Apache Storm
Apache Storm is a distributed real-time computation system designed for processing large streams of data with low latency and high fault tolerance.
- F. None of above. chosen
Statements (50)
| Predicate | Object |
|---|---|
| instanceOf |
Apache Kafka ecosystem component
ⓘ
Java library ⓘ stream processing library ⓘ |
| builtOnTopOf | Apache Kafka NERFINISHED ⓘ |
| deploymentModel |
embedded in client applications
ⓘ
no separate processing cluster required ⓘ |
| designedFor |
building real-time applications
ⓘ
distributed stream processing ⓘ event-driven microservices ⓘ stateful stream processing ⓘ |
| developedBy | Apache Software Foundation NERFINISHED ⓘ |
| documentationURL | https://kafka.apache.org/documentation/streams ⓘ |
| domain |
event streaming
ⓘ
real-time data processing ⓘ stream processing ⓘ |
| introducedIn | Apache Kafka 0.10 NERFINISHED ⓘ |
| license | Apache License 2.0 ⓘ |
| officialWebsite | https://kafka.apache.org/streams ⓘ |
| partOf | Apache Kafka NERFINISHED ⓘ |
| persistsStateTo | Kafka changelog topics NERFINISHED ⓘ |
| programmingLanguage | Java ⓘ |
| provides |
GlobalKTable abstraction
ⓘ
KStream abstraction ⓘ KTable abstraction ⓘ high-level DSL ⓘ low-level Processor API ⓘ |
| runsOn | Java Virtual Machine NERFINISHED ⓘ |
| scalesBy | Kafka topic partitioning ⓘ |
| storesStateIn | RocksDB NERFINISHED ⓘ |
| supports |
at-least-once processing semantics
ⓘ
event-time processing ⓘ exactly-once processing semantics ⓘ exactly-once-v2 semantics in newer Kafka versions ⓘ fault tolerance ⓘ interactive queries ⓘ joins between streams ⓘ joins between streams and tables ⓘ local state stores ⓘ processing-time processing ⓘ repartitioning of streams ⓘ stateful transformations ⓘ stateless transformations ⓘ topology-based processing model ⓘ windowed aggregations ⓘ |
| supportsProgrammingLanguage |
Java
NERFINISHED
ⓘ
Kotlin NERFINISHED ⓘ Scala NERFINISHED ⓘ |
| uses |
Kafka consumer API
NERFINISHED
ⓘ
Kafka producer API NERFINISHED ⓘ Kafka topics ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Kafka Streams Description of subject: Kafka Streams is a Java library for building real-time, distributed stream processing applications on top of Apache Kafka.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.