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Datadog

Developer Platforms & InfraLast updated: 2026-06-10

Datadog is an observability platform, reviewed for telemetry data, monitoring, sharing, tracking, retention, and organization controls.

ScoreLatest FindingScore BreakdownSource & EvidenceCompanyAlternatives
ScoreLatest FindingScore BreakdownSource & EvidenceCompanyAlternatives

55

Weak

Mixed
Weak
Poor
Mixed
Good

Overall Score

55

Weak

AI Training:60
Mixed
Data Sharing:55
Weak
Ads & Tracking:35
Poor
Data Retention:60
Mixed
User Control:75
Good

Overall Score

55

Weak

AI Training:60
Mixed
Data Sharing:55
Weak
Ads & Tracking:35
Poor
Data Retention:60
Mixed
User Control:75
Good

Latest Policy Findings: 2026-06-10

Datadog combines broad tracking with unusually strong privacy controls.

Strongest: User Control
75/100

Datadog gives users more direct privacy control than its other categories, especially around data export and clear admin controls.

Weakest: Ads & Tracking
35/100

Datadog is weakest on ads and tracking because behavioral signals can still travel through analytics or partner tools.

Recommended Action:

Score Breakdown:

AI Training

60

Mixed

60

Mixed

The reviewed policy does not provide a simple no-AI-training promise for all telemetry and event data.

-20Source [1]

Datadog uses collected information to improve existing products and create new ones.

-20Source [2]

Datadog publishes privacy-policy coverage for monitoring services and account data.

+20Source [3]

Admins can control what telemetry is ingested in the first place through instrumentation and scrubbing choices.

+20Source [4]

Datadog supports access and configuration controls that can narrow which users see collected telemetry.

+20Source [5]

Data Sharing

55

Weak

55

Weak

Telemetry can still flow through integrations, cloud providers, subprocessors, organization users, and legal disclosures.

-25Source [6]

Marketing, analytics, and social-sharing features widen the sharing surface beyond core monitoring.

-20Source [7]

Datadog documents privacy rights and service-provider handling.

+15Source [8]

Admins can govern access, archives, and integrations for observability data.

+15Source [9]

Datadog documents account-management and rights-request paths for personal information.

+10Source [10]

Security-focused processing is clearly called out instead of being hidden in vague operational language.

+15Source [11]

Ads & Tracking

35

Poor

35

Poor

Analytics and observability tools can collect identifiers, events, session replays, logs, traces, device data, and usage metadata.

-35Source [12]

Teams can reduce exposure with masking, consent mode, sampling, log scrubbing, retention controls, and restricted access.

+20Source [13]

Data Retention

60

Mixed

60

Mixed

Retention still depends on product, plan, archive settings, backups, and legal needs.

-20Source [14]

Observability exports and integrations can preserve copies of telemetry outside the main workspace lifecycle.

-20Source [15]

Retention can be configured by product and plan for many telemetry types.

+20Source [16]

Admins can manage archives and access in ways that affect how long sensitive telemetry remains easily available.

+15Source [17]

Datadog says it keeps personal information only as long as necessary, then deletes or archives it unless there is a lawful reason to retain it.

+15Source [18]

Rights-request and access paths are documented.

+10Source [19]

User Control

75

Good

75

Good

Admins can manage data scrubbing, access, retention, archives, and integrations.

+25Source [20]

Customers can update account information, access rights, and portability requests.

+20Source [21]

Instrumentation hygiene lets teams decide what sensitive data never enters Datadog.

+15Source [22]

Security contact and abuse-report paths are clearly documented.

+15Source [23]

Privacy still depends on whether teams scrub sensitive data before sending it.

-15Source [24]

End-user visibility into collected telemetry is much weaker than administrator control.

-10Source [25]

Source & Evidence Links:

Sources:

Legal Privacy Policy

Open: datadoghq.com

Latest Finding

Open: support.google.com

Evidence:

1. AI Use

The reviewed policy does not provide a simple no-AI-training promise for all telemetry and event data.

Open: datadoghq.com

2. Datadog Uses

Datadog uses collected information to improve existing products and create new ones.

Open: datadoghq.com

3. Datadog Publishes

Datadog publishes privacy-policy coverage for monitoring services and account data.

Open: datadoghq.com

4. Controls

Admins can control what telemetry is ingested in the first place through instrumentation and scrubbing choices.

Open: datadoghq.com

5. Controls

Datadog supports access and configuration controls that can narrow which users see collected telemetry.

Open: datadoghq.com

Company Details:

Founded

Jan 2010

Founder

Olivier Pomel and Alexis Le-Quoc

Parent Company

Datadog

Lifecycle

Active

Category

Developer Platforms & Infra

CEO

Olivier Pomel

Security Team

In house

Date Added

06-10-2026

Alternatives:

Netlify

Developer Tools

70

Mixed

Docker logo

Docker

Developer Tools

60

Mixed

Vercel logo

Vercel

Developer Tools

65

Mixed

Bitbucket

Developer Tools

70

Mixed

Stack Overflow for Teams

Developer Tools

65

Mixed

New Relic

Developer Tools

55

Weak