Datadog
E426146
Datadog is a cloud-based monitoring and security platform that provides observability into applications, infrastructure, logs, and metrics for modern DevOps and IT teams.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Datadog canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4280012 — 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: Datadog Context triple: [Amazon Kinesis Data Firehose, integratesWith, Datadog]
-
A.
New Relic
New Relic is a software analytics and application performance monitoring company that provides tools for tracking and optimizing the performance of web and mobile applications.
-
B.
AppDynamics
AppDynamics is an application performance monitoring and observability company that provides tools to track, analyze, and optimize the performance of software applications and IT infrastructure.
-
C.
Sumo Logic
Sumo Logic is a cloud-native machine data analytics and log management platform that helps organizations monitor, troubleshoot, and secure their applications and infrastructure in real time.
-
D.
Amazon CloudWatch
Amazon CloudWatch is a monitoring and observability service that collects and analyzes logs, metrics, and events from AWS resources and applications to help track performance and operational health.
-
E.
Looker
Looker is a modern business intelligence and data analytics platform that enables organizations to explore, visualize, and share insights from their data.
- 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: Datadog Target entity description: Datadog is a cloud-based monitoring and security platform that provides observability into applications, infrastructure, logs, and metrics for modern DevOps and IT teams.
-
A.
New Relic
New Relic is a software analytics and application performance monitoring company that provides tools for tracking and optimizing the performance of web and mobile applications.
-
B.
AppDynamics
AppDynamics is an application performance monitoring and observability company that provides tools to track, analyze, and optimize the performance of software applications and IT infrastructure.
-
C.
Sumo Logic
Sumo Logic is a cloud-native machine data analytics and log management platform that helps organizations monitor, troubleshoot, and secure their applications and infrastructure in real time.
-
D.
Amazon CloudWatch
Amazon CloudWatch is a monitoring and observability service that collects and analyzes logs, metrics, and events from AWS resources and applications to help track performance and operational health.
-
E.
Looker
Looker is a modern business intelligence and data analytics platform that enables organizations to explore, visualize, and share insights from their data.
- F. None of above. chosen
Statements (55)
| Predicate | Object |
|---|---|
| instanceOf |
Cloud monitoring platform
ⓘ
Company ⓘ Software-as-a-Service platform ⓘ |
| country |
United States of America
ⓘ
surface form:
United States
|
| deploymentModel | Software as a Service ⓘ |
| foundedBy |
Alexis Lê-Quôc
NERFINISHED
ⓘ
Olivier Pomel NERFINISHED ⓘ |
| hasFeature |
Alerting and notifications
ⓘ
Custom dashboards ⓘ Distributed tracing ⓘ Log correlation with metrics and traces ⓘ Machine-learning based anomaly detection ⓘ |
| headquartersLocation |
New York
NERFINISHED
ⓘ
New York City ⓘ United States of America ⓘ
surface form:
United States
|
| inception | 2010 ⓘ |
| industry |
Application performance monitoring
ⓘ
Cloud infrastructure monitoring ⓘ Cybersecurity ⓘ Log management ⓘ Observability ⓘ |
| integratesWith |
Amazon Web Services
NERFINISHED
ⓘ
Docker NERFINISHED ⓘ Google Cloud Platform NERFINISHED ⓘ Kubernetes NERFINISHED ⓘ Microsoft Azure NERFINISHED ⓘ |
| IPODate | 2019 ⓘ |
| legalForm | Public company ⓘ |
| offers |
Application performance monitoring (APM)
ⓘ
Cloud infrastructure monitoring ⓘ Cloud security posture management ⓘ Container monitoring ⓘ Dashboards and visualization ⓘ Database monitoring ⓘ Incident management tools ⓘ Infrastructure as code security ⓘ Kubernetes monitoring ⓘ Log analytics ⓘ Log management ⓘ Metrics collection and analytics ⓘ Network performance monitoring ⓘ Real user monitoring (RUM) ⓘ Security monitoring ⓘ Serverless monitoring ⓘ Synthetic monitoring ⓘ |
| stockExchange | Nasdaq NERFINISHED ⓘ |
| supports |
Hybrid cloud environments
ⓘ
Multi-cloud environments ⓘ On-premises infrastructure ⓘ |
| targetAudience |
DevOps teams
ⓘ
IT operations teams ⓘ Security teams ⓘ Software engineering teams ⓘ |
| tickerSymbol | DDOG NERFINISHED ⓘ |
| website | https://www.datadoghq.com ⓘ |
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: Datadog Description of subject: Datadog is a cloud-based monitoring and security platform that provides observability into applications, infrastructure, logs, and metrics for modern DevOps and IT teams.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.