Datadog Secret Scanning

Name: Datadog Secret Scanning
Brand: Datadog

Leader

Datadog provides cloud-scale monitoring and security for metrics, traces and logs in one unified platform.

Est 2010|Valuation $91.4B|Raised $795.9M

LinkedIn 546K|Website|Web traffic 4.6M|FTEs 8,100|HQ New York, New York, US

MarketsApplication Security Testing (AST)Secret Scanning

01Competitive Landscape

Narrative analysis

Datadog's differentiated positioning: - The vendor positions Secret Scanning as integrated into the Datadog platform, enabling correlation between code findings and runtime/infra signals. Where dedicated secrets vendors may excel (GitGuardian, TruffleHog, etc.): - Secrets-first tooling often emphasizes: - broad detection libraries, - program management features (remediation playbooks, metrics), - scanning beyond repositories (for example, collaboration tools) depending on the product, - a focus on secrets governance. Where native VCS features can be preferable (GitHub Advanced Security / GitLab): - If most repositories are hosted on a single platform, native secret scanning can reduce operational complexity and administrative overhead. Pricing/value considerations: - Community commentary frequently describes Datadog as costly; even if Secret Scanning is competitively priced on a per-committer basis, cumulative platform spend and multiple pricing axes can be significant factors in procurement decisions.

	Datadog Secret Scanning	GitGuardian (Internal Secrets Monitoring)	Snyk (platform)
Starting price	Published per-committer starting pricing available from the vendor	Published free tier for individuals/small teams; paid tiers require vendor contact	Public plans exist; pricing varies by product; enterprise often custom
Recommended use case	Organizations using Datadog that want code-to-runtime correlation and centralized security workflows	Teams focused on a dedicated secrets program with emphasis on secrets sprawl	Organizations standardizing on a DevSecOps platform covering SCA/SAST/container/IaC
Notable strengths	Integration with Datadog platform telemetry; CI/VCS gating; vendor-stated credential validation	Secrets-first feature set and program-oriented workflows (per vendor documentation)	Broad application security coverage and ecosystem integrations
Notable limitations	Adds a cost dimension; limited independent feature-specific review coverage; potential for increased vendor coupling	Enterprise pricing and overlap with platform-native scanning may be concerns	Pricing, limits, and complexity can be constraints for some teams

01Competitive Landscape

Narrative analysis

Datadog's differentiated positioning:

The vendor positions Secret Scanning as integrated into the Datadog platform, enabling correlation between code findings and runtime/infra signals.

Where dedicated secrets vendors may excel (GitGuardian, TruffleHog, etc.):

Secrets-first tooling often emphasizes:
- broad detection libraries,
- program management features (remediation playbooks, metrics),
- scanning beyond repositories (for example, collaboration tools) depending on the product,
- a focus on secrets governance.

Where native VCS features can be preferable (GitHub Advanced Security / GitLab):

If most repositories are hosted on a single platform, native secret scanning can reduce operational complexity and administrative overhead.

Pricing/value considerations:

Community commentary frequently describes Datadog as costly; even if Secret Scanning is competitively priced on a per-committer basis, cumulative platform spend and multiple pricing axes can be significant factors in procurement decisions.

	Datadog Secret Scanning	GitGuardian (Internal Secrets Monitoring)	Snyk (platform)
Starting price	Published per-committer starting pricing available from the vendor	Published free tier for individuals/small teams; paid tiers require vendor contact	Public plans exist; pricing varies by product; enterprise often custom
Recommended use case	Organizations using Datadog that want code-to-runtime correlation and centralized security workflows	Teams focused on a dedicated secrets program with emphasis on secrets sprawl	Organizations standardizing on a DevSecOps platform covering SCA/SAST/container/IaC
Notable strengths	Integration with Datadog platform telemetry; CI/VCS gating; vendor-stated credential validation	Secrets-first feature set and program-oriented workflows (per vendor documentation)	Broad application security coverage and ecosystem integrations
Notable limitations	Adds a cost dimension; limited independent feature-specific review coverage; potential for increased vendor coupling	Enterprise pricing and overlap with platform-native scanning may be concerns	Pricing, limits, and complexity can be constraints for some teams