Apache Cassandra
E358077
Apache Cassandra is a highly scalable, distributed NoSQL database designed for handling large amounts of data across many commodity servers with high availability and no single point of failure.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Apache Cassandra canonical | 5 |
How this entity was disambiguated
This entity first appeared as the object of triple T3418863 — 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 Cassandra Context triple: [Apache Software Foundation, overseesProject, Apache Cassandra]
-
A.
Apache HBase
Apache HBase is a distributed, scalable, NoSQL database designed for real-time read/write access to large datasets, typically running on top of the Hadoop ecosystem.
-
B.
Apache Hive
Apache Hive is a data warehouse and SQL-like query system built on top of Hadoop for managing and analyzing large datasets stored in distributed storage.
-
C.
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.
-
D.
Amazon Neptune
Amazon Neptune is a fully managed graph database service designed for storing and querying highly connected data using popular graph models and query languages.
-
E.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
- 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 Cassandra Target entity description: Apache Cassandra is a highly scalable, distributed NoSQL database designed for handling large amounts of data across many commodity servers with high availability and no single point of failure.
-
A.
Apache HBase
Apache HBase is a distributed, scalable, NoSQL database designed for real-time read/write access to large datasets, typically running on top of the Hadoop ecosystem.
-
B.
Apache Hive
Apache Hive is a data warehouse and SQL-like query system built on top of Hadoop for managing and analyzing large datasets stored in distributed storage.
-
C.
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.
-
D.
Amazon Neptune
Amazon Neptune is a fully managed graph database service designed for storing and querying highly connected data using popular graph models and query languages.
-
E.
Hadoop
Hadoop is an open-source framework that enables distributed storage and parallel processing of large data sets across clusters of commodity hardware.
- F. None of above. chosen
Statements (52)
| Predicate | Object |
|---|---|
| instanceOf |
NoSQL database
ⓘ
distributed database ⓘ open-source software ⓘ wide-column store ⓘ |
| abbreviation |
Apache Cassandra CQL
ⓘ
surface form:
CQL
|
| architecture | peer-to-peer ⓘ |
| category |
NoSQL database management system
ⓘ
free database management system ⓘ |
| consistencyModel | AP in CAP theorem with tunable consistency ⓘ |
| designedFor |
fault tolerance
ⓘ
handling large amounts of data ⓘ high availability ⓘ horizontal scalability ⓘ |
| developer | Apache Software Foundation ⓘ |
| feature |
automatic data partitioning
ⓘ
eventual consistency ⓘ gossip protocol for cluster membership ⓘ lightweight transactions ⓘ linear scalability ⓘ log-structured storage ⓘ materialized views ⓘ no single point of failure ⓘ pluggable replication strategies ⓘ replication across data centers ⓘ secondary indexes ⓘ snitch for topology awareness ⓘ tunable consistency ⓘ write-optimized storage engine ⓘ |
| implements | Paxos-based lightweight transactions ⓘ |
| initialReleaseYear | 2008 ⓘ |
| license | Apache License 2.0 ⓘ |
| originalDeveloper | Facebook ⓘ |
| programmingLanguage | Java ⓘ |
| repository | https://github.com/apache/cassandra ⓘ |
| runsOn |
Linux
ⓘ
Windows ⓘ macOS ⓘ |
| stableReleaseMajorVersion | 5 ⓘ |
| storageModel | SSTable-based ⓘ |
| supports |
OLTP workloads
ⓘ
multi-data-center replication ⓘ rack-aware replication ⓘ time-series workloads ⓘ |
| supportsModel | wide-column data model ⓘ |
| supportsQueryLanguage |
Apache Cassandra CQL
ⓘ
surface form:
Cassandra Query Language
|
| usedFor |
IoT data storage
ⓘ
messaging and logging backends ⓘ real-time analytics ⓘ |
| uses |
SSTables
ⓘ
commit log ⓘ memtables ⓘ |
| website | https://cassandra.apache.org ⓘ |
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 Cassandra Description of subject: Apache Cassandra is a highly scalable, distributed NoSQL database designed for handling large amounts of data across many commodity servers with high availability and no single point of failure.
Referenced by (5)
Full triples — surface form annotated when it differs from this entity's canonical label.