MongoDB database
E360848
MongoDB database is a popular open-source NoSQL document-oriented database designed for scalability, flexibility, and high performance in modern applications.
All labels observed (3)
| Label | Occurrences |
|---|---|
| MongoDB | 16 |
| MongoDB database canonical | 2 |
| MongoDB open-source project | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3482237 — 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.
Target entity: MongoDB database Context triple: [MongoDB Inc., product, MongoDB database]
-
A.
Mongo
Mongo is the nickname of Steve "Mongo" McMichael, a former NFL defensive tackle and professional wrestler best known for his time with the Chicago Bears and WCW.
-
B.
Amazon DocumentDB
Amazon DocumentDB is a fully managed, scalable document database service from AWS designed to be compatible with MongoDB workloads and optimized for performance, durability, and security in the cloud.
-
C.
MariaDB
MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
-
D.
Azure Cosmos DB
Azure Cosmos DB is a globally distributed, multi-model NoSQL database service designed for low-latency, scalable applications in the cloud.
-
E.
DB
DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: MongoDB database Target entity description: MongoDB database is a popular open-source NoSQL document-oriented database designed for scalability, flexibility, and high performance in modern applications.
-
A.
Mongo
Mongo is the nickname of Steve "Mongo" McMichael, a former NFL defensive tackle and professional wrestler best known for his time with the Chicago Bears and WCW.
-
B.
Amazon DocumentDB
Amazon DocumentDB is a fully managed, scalable document database service from AWS designed to be compatible with MongoDB workloads and optimized for performance, durability, and security in the cloud.
-
C.
MariaDB
MariaDB is an open-source relational database management system, forked from MySQL, known for its compatibility, performance, and community-driven development.
-
D.
Azure Cosmos DB
Azure Cosmos DB is a globally distributed, multi-model NoSQL database service designed for low-latency, scalable applications in the cloud.
-
E.
DB
DB is the commonly used abbreviation for Deutsche Bahn, Germany’s national railway company and one of the largest rail operators in Europe.
- F. None of above. chosen
Statements (89)
| Predicate | Object |
|---|---|
| instanceOf |
NoSQL database
ⓘ
database management system ⓘ document-oriented database ⓘ open-source software ⓘ |
| abbreviation | MQL ⓘ |
| category | NoSQL database ⓘ |
| dataModel | document model ⓘ |
| defaultStorageEngine | WiredTiger ⓘ |
| developer | MongoDB Inc. ⓘ |
| hasCloudService |
MongoDB Cloud
ⓘ
surface form:
MongoDB Atlas
|
| hasEdition |
Atlas cloud service
ⓘ
Community Server ⓘ Enterprise Server ⓘ |
| hasGUIClient | MongoDB Compass ⓘ |
| hasOfficialShell | mongosh ⓘ |
| initialReleaseDate | 2009-02-11 ⓘ |
| license | Server Side Public License ⓘ |
| optimizedFor |
flexible schemas
ⓘ
high write throughput ⓘ horizontal scalability ⓘ |
| previousShell | mongo shell ⓘ |
| storesDataAs | BSON documents ⓘ |
| supportsAuthenticationMechanism |
Kerberos
ⓘ
LDAP integration ⓘ SCRAM-SHA-1 ⓘ SCRAM-SHA-256 ⓘ x.509 certificates ⓘ |
| supportsDataType |
arrays
ⓘ
binary data ⓘ dates ⓘ embedded documents ⓘ geospatial data ⓘ |
| supportsDeploymentModel |
cloud
ⓘ
on-premises ⓘ |
| supportsFeature |
GridFS
ⓘ
TLS encryption in transit ⓘ TTL indexes ⓘ aggregation framework ⓘ automatic failover ⓘ change streams ⓘ encryption at rest ⓘ full-text search ⓘ horizontal scaling ⓘ multi-document ACID transactions ⓘ multi-document joins via $lookup ⓘ read preferences ⓘ replica sets ⓘ role-based access control ⓘ schema validation ⓘ sharding ⓘ time series collections ⓘ transactions ⓘ write concern levels ⓘ |
| supportsIndexing |
compound indexes
ⓘ
geospatial indexes ⓘ hashed indexes ⓘ single-field indexes ⓘ text indexes ⓘ wildcard indexes ⓘ |
| supportsOperatingSystem |
Linux
ⓘ
Windows ⓘ macOS ⓘ |
| supportsProgrammingLanguageDriver |
C# programming language
ⓘ
surface form:
C#
C++ ⓘ Go ⓘ Java ⓘ JavaScript ⓘ Node.js ⓘ PHP ⓘ Python ⓘ Ruby ⓘ Rust ⓘ Scala ⓘ |
| supportsQueryLanguage | MongoDB Query Language ⓘ |
| supportsReplicationMode |
primary-secondary
ⓘ
primary-secondary-arbiter ⓘ |
| supportsShardingStrategy |
hash-based sharding
ⓘ
range-based sharding ⓘ zone sharding ⓘ |
| supportsStorageEngine |
WiredTiger
ⓘ
in-memory storage engine ⓘ |
| usedFor |
IoT data storage
ⓘ
content management ⓘ mobile applications ⓘ real-time analytics ⓘ web applications ⓘ |
| writtenInLanguage |
C
ⓘ
C++ ⓘ JavaScript ⓘ |
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.
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.
Subject: MongoDB database Description of subject: MongoDB database is a popular open-source NoSQL document-oriented database designed for scalability, flexibility, and high performance in modern applications.
Referenced by (19)
Full triples — surface form annotated when it differs from this entity's canonical label.