Apache Storm
E185674
big data technology
distributed real-time computation system
open-source software
stream processing framework
Apache Storm is a distributed real-time computation system designed for processing large streams of data with low latency and high fault tolerance.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Apache Storm canonical | 13 |
| Apache Storm (via integration) | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1647852 — 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 Storm Context triple: [Hadoop, influenced, Apache Storm]
-
A.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
B.
Apache Mesos
Apache Mesos is an open-source cluster manager that abstracts CPU, memory, storage, and other resources away from machines to enable efficient deployment and scaling of distributed applications and frameworks.
-
C.
Google Cloud Dataflow
Google Cloud Dataflow is a fully managed service for developing and executing batch and streaming data processing pipelines, based on Apache Beam, within the Google Cloud ecosystem.
-
D.
Jepsen
Jepsen is a surname most notably associated with individuals such as display technology innovator Mary Lou Jepsen.
-
E.
Paxos consensus algorithm
The Paxos consensus algorithm is a fault-tolerant protocol for achieving agreement among distributed systems, widely used as a foundation for reliable, replicated state machines and modern distributed databases.
- 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 Storm Target entity description: Apache Storm is a distributed real-time computation system designed for processing large streams of data with low latency and high fault tolerance.
-
A.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
-
B.
Apache Mesos
Apache Mesos is an open-source cluster manager that abstracts CPU, memory, storage, and other resources away from machines to enable efficient deployment and scaling of distributed applications and frameworks.
-
C.
Google Cloud Dataflow
Google Cloud Dataflow is a fully managed service for developing and executing batch and streaming data processing pipelines, based on Apache Beam, within the Google Cloud ecosystem.
-
D.
Jepsen
Jepsen is a surname most notably associated with individuals such as display technology innovator Mary Lou Jepsen.
-
E.
Paxos consensus algorithm
The Paxos consensus algorithm is a fault-tolerant protocol for achieving agreement among distributed systems, widely used as a foundation for reliable, replicated state machines and modern distributed databases.
- F. None of above. chosen
Statements (82)
| Predicate | Object |
|---|---|
| instanceOf |
big data technology
ⓘ
distributed real-time computation system ⓘ open-source software ⓘ stream processing framework ⓘ |
| competesWith |
Apache Flink
ⓘ
Apache Samza ⓘ Apache Spark Streaming ⓘ
linked to:
Apache Spark
Kafka Streams ⓘ |
| designedFor | processing large streams of data ⓘ |
| developedBy |
BackType
ⓘ
Nathan Marz ⓘ Twitter ⓘ
linked to:
Twitter, Inc.
|
| hasComponent |
bolt
ⓘ
spout ⓘ stream ⓘ topology ⓘ tuple ⓘ |
| hasFeature |
automatic fault detection
ⓘ
automatic task reassignment ⓘ backpressure ⓘ distributed mode for production ⓘ dynamic topology rebalancing ⓘ guaranteed message processing ⓘ local mode for development ⓘ metrics collection ⓘ pluggable schedulers ⓘ pluggable serialization ⓘ |
| hasProperty |
high fault tolerance
ⓘ
low latency ⓘ |
| hasReleaseType | open source ⓘ |
| license | Apache License 2.0 ⓘ |
| maintainedBy | Apache Software Foundation ⓘ |
| partOf | Apache Software Foundation projects ⓘ |
| runsOn |
JVM
ⓘ
linked to:
Java Virtual Machine
|
| supports |
at-least-once processing semantics
ⓘ
cloud deployment ⓘ cluster deployment ⓘ distributed computation ⓘ event-time processing ⓘ exactly-once processing semantics ⓘ horizontal scalability ⓘ on-premises deployment ⓘ real-time stream processing ⓘ reliable message processing ⓘ stateful stream processing ⓘ |
| supportsIntegrationWith |
Amazon Kinesis
ⓘ
Apache Cassandra ⓘ Apache HBase ⓘ Apache Hadoop ⓘ
linked to:
Hadoop
Apache Kafka ⓘ Elasticsearch ⓘ JMS ⓘ Kestrel ⓘ MongoDB ⓘ
linked to:
MongoDB database
RabbitMQ ⓘ Redis ⓘ Storm UI ⓘ |
| supportsLanguage |
Clojure
ⓘ
Java ⓘ Python ⓘ Ruby ⓘ Scala ⓘ any language via Thrift ⓘ |
| usedFor |
ETL processing
ⓘ
clickstream analysis ⓘ continuous computation ⓘ fraud detection ⓘ log processing ⓘ monitoring and alerting ⓘ online machine learning ⓘ real-time analytics ⓘ sensor data processing ⓘ social media analytics ⓘ |
| uses |
Executors
ⓘ
Nimbus ⓘ Supervisors ⓘ Tasks ⓘ Workers ⓘ ZooKeeper ⓘ
linked to:
Apache ZooKeeper
|
| website | https://storm.apache.org/ ⓘ |
| writtenInLanguage |
Clojure
ⓘ
Java ⓘ |
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 Storm Description of subject: Apache Storm is a distributed real-time computation system designed for processing large streams of data with low latency and high fault tolerance.
Referenced by (14)
Full triples — surface form annotated when it differs from this entity's canonical label.