Apache Kafka
E358076
Apache Kafka is a distributed event streaming platform widely used for building real-time data pipelines and streaming applications.
All labels observed (5)
| Label | Occurrences |
|---|---|
| Apache Kafka canonical | 26 |
| Apache Kafka 0.10 | 1 |
| Apache Kafka protocol | 1 |
| IBM Event Streams | 1 |
| Kafka protocol (via Event Streams) | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3418862 — 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: Apache Kafka Context triple: [Apache Software Foundation, overseesProject, Apache Kafka]
-
A.
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.
-
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.
Apache ZooKeeper
Apache ZooKeeper is a centralized service for maintaining configuration information, naming, and distributed synchronization in large-scale distributed systems.
-
D.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
-
E.
Apache Flume
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log and event data into Hadoop and other data stores.
- 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: Apache Kafka Target entity description: Apache Kafka is a distributed event streaming platform widely used for building real-time data pipelines and streaming applications.
-
A.
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.
-
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.
Apache ZooKeeper
Apache ZooKeeper is a centralized service for maintaining configuration information, naming, and distributed synchronization in large-scale distributed systems.
-
D.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
-
E.
Apache Flume
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log and event data into Hadoop and other data stores.
- F. None of above. chosen
Statements (62)
| Predicate | Object |
|---|---|
| instanceOf |
distributed event streaming platform
ⓘ
open-source software ⓘ stream processing software ⓘ |
| category |
data streaming platform
ⓘ
message-oriented middleware ⓘ |
| designGoal |
durability
ⓘ
fault tolerance ⓘ high throughput ⓘ low latency ⓘ scalability ⓘ |
| developer | Apache Software Foundation ⓘ |
| hasComponent |
Kafka Connect
ⓘ
Kafka Streams ⓘ Kafka broker ⓘ Kafka consumer ⓘ Kafka partition ⓘ Kafka producer ⓘ Kafka topic ⓘ ZooKeeper (legacy dependency) ⓘ
linked to:
Apache ZooKeeper
|
| initialReleaseDate | 2011 ⓘ |
| license | Apache License 2.0 ⓘ |
| originalDeveloper | LinkedIn ⓘ |
| partOf | Apache Software Foundation projects ⓘ |
| programmingLanguage |
Java
ⓘ
Scala ⓘ |
| replacedByInMetadataManagement | KRaft mode ⓘ |
| repository | https://github.com/apache/kafka ⓘ |
| supports |
at-least-once delivery semantics
ⓘ
event streaming ⓘ exactly-once processing semantics ⓘ fault tolerance ⓘ horizontal scalability ⓘ log aggregation ⓘ message queuing ⓘ partitioned topics ⓘ publish-subscribe messaging ⓘ real-time analytics ⓘ real-time data pipelines ⓘ replication ⓘ stream processing ⓘ |
| supportsClient |
C# client
ⓘ
C/C++ client ⓘ Go client ⓘ Java client ⓘ Python client ⓘ |
| supportsProtocol |
TCP
ⓘ
linked to:
Transmission Control Protocol
|
| supportsSecurityFeature |
ACL-based authorization
ⓘ
SASL authentication ⓘ SSL/TLS encryption ⓘ |
| useCase |
ETL pipelines
ⓘ
IoT data ingestion ⓘ building event-driven architectures ⓘ data integration ⓘ log and metrics collection ⓘ microservices communication ⓘ |
| usedBy |
Airbnb
ⓘ
LinkedIn ⓘ Netflix ⓘ Uber ⓘ |
| website | https://kafka.apache.org ⓘ |
| writtenIn |
Java
ⓘ
Scala ⓘ |
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: Apache Kafka Description of subject: Apache Kafka is a distributed event streaming platform widely used for building real-time data pipelines and streaming applications.
Referenced by (30)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Apache Kafka
subject linked to:
Mesos
linked to: Apache Kafka
linked to: Apache Kafka
linked to: Apache Kafka