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Developer Tools · head to head

Namespace vs Securiti

Namespace logo

Namespace

Developer Tools

The dev platform for the next 100 billion commits

From
Free
Free plan
Yes
Securiti logo

Securiti

Cybersecurity

Data and AI security posture management with privacy operations on a single data catalogue

From
On request
Free plan
No

The short version

  • Only Namespace has a free tier, so it costs nothing to try first.
  • Each has a real cost: Namespace developer plan is pay-as-you-go only; minimum usage unclear; Securiti value depends entirely on connector coverage and completed scanning, so the first useful data map commonly takes months and stalls whenever a data owner will not grant access to a system.
  • They diverge on capability: Namespace covers Devboxes, Securiti covers Sensitive data discovery.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Namespace and Securiti actually diverge.

Attributes where Namespace and Securiti differ
AttributeNamespaceSecuriti
Starting priceFreeOn request
Pricing modelUnknownquote
Free tierYesNo
PlatformsCloud, Mac, Windows, LinuxWeb
CategoryDeveloper ToolsCybersecurity

Identical on both: user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Namespace

  • Devboxes
  • GitHub Actions runners
  • Docker builds
  • Cross-invocation caching
  • NVMe storage
  • High-speed networking
  • Multiple OS support
  • Bazel and Turborepo support

Only in Securiti

  • Sensitive data discovery
  • Data security posture management
  • Data access intelligence
  • AI and LLM governance
  • PrivacyOps
  • Data flow governance
  • Breach impact analysis
  • People data graph

What people use each for

The jobs each tool is most often brought in to do.

Namespace

  • Providing AI coding agents with cloud-based development environmentsnot Securiti
  • Accelerating CI builds with faster GitHub Actions runnersnot Securiti
  • Distributing builds across teams with managed infrastructurenot Securiti
  • Scaling development velocity for monorepo organizationsnot Securiti

Securiti

  • An enterprise that must answer, within days of a breach, exactly whose regulated data was in the affected store and in which jurisdictionsnot Namespace
  • A privacy team automating deletion requests across dozens of systems where the hard part is knowing where a person appears at allnot Namespace
  • A security team that needs to find sensitive data sitting in over-permissive cloud buckets and warehouse tables before an auditor doesnot Namespace
  • A company putting internal data into retrieval-augmented AI applications and needing to prove that regulated fields are not reaching the modelnot Namespace

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Namespace

  • Developer plan is pay-as-you-go only; minimum usage unclear
  • Team plan $100/mo is competitive but usage limits may be tight
  • Devbox pricing separate at $0.004/minute could add up quickly
  • Enterprise plan requires custom sales conversation

Securiti

  • Value depends entirely on connector coverage and completed scanning, so the first useful data map commonly takes months and stalls whenever a data owner will not grant access to a system.
  • Usage-based pricing tied to data volume means costs rise as the estate grows rather than as the security programme matures, and organisations with large but low-risk data lakes pay for scanning they do not need.
  • The breadth across DSPM, privacy and AI governance means each individual module is competing with a specialist, and buyers who only need one of the three often find a focused tool does that job better for less.
  • Classification accuracy on unstructured and free-text data requires tuning, and untuned deployments generate false positives that erode trust in the catalogue precisely when teams are being asked to act on it.
  • Pricing is unpublished and modular, so scoping is difficult without a sales engagement and the eventual cost depends on module choices that are hard to evaluate before you have seen your own data map.

Pricing, plan by plan

Namespace

Free
  • DeveloperFree
    • Pay-as-you-go
    • On-demand compute
    • Docker builds
  • Team$100/month
    • 100,000 unit minutes
    • 1,000 Docker builds
    • Everything in Developer
  • Business$250/month
    • 250,000 unit minutes
    • 2,500 Docker builds
    • Everything in Team
  • Enterprise$undefined/custom
    • Custom compute/Docker build limits
    • Audit log export
    • Enterprise SSO

Securiti

On request
  • Data and AI Command Centre$undefined/year
    • Modular, usage based pricing quoted by data volume and modules selected
    • Available through the AWS marketplace as well as direct
    • Annual subscription with no fixed end date, cancellable

Which should you pick?

Choose Namespace if

  • You need devboxes.
  • You want to start without paying.
  • You work on Cloud, Mac, Windows, Linux.
  • You also want github actions runners.

Choose Securiti if

  • You need sensitive data discovery.
  • You also want data security posture management.

Questions people ask

Is Namespace or Securiti better?
Neither clearly leads. Namespace starts at Free and Securiti at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Namespace or Securiti?
Namespace has a free tier; the other does not. Paid plans start at Free for Namespace and On request for Securiti.
Does Namespace or Securiti run on more platforms?
Namespace runs on Cloud, Mac, Windows, Linux. Securiti runs on Web.
Can I use Namespace for free?
Yes. Namespace has a free tier, so you can try it without paying. Securiti starts at On request.
What is Namespace best used for?
Namespace is most often used for providing ai coding agents with cloud-based development environments, accelerating ci builds with faster github actions runners, distributing builds across teams with managed infrastructure, scaling development velocity for monorepo organizations. Of those, providing ai coding agents with cloud-based development environments and accelerating ci builds with faster github actions runners are not what Securiti is typically brought in for.
What can Namespace do that Securiti cannot?
Namespace covers Devboxes, GitHub Actions runners, Docker builds, Cross-invocation caching. Securiti covers Sensitive data discovery, Data security posture management, Data access intelligence, AI and LLM governance.

Answered from the vendors’ own pages

Namespace: How is compute usage metered on the Developer plan?

Developer plan uses pay-as-you-go billing. Devboxes bill at $0.004 per minute. Storage and caching services have separate usage-based fees. A 30-day free trial is available to test usage patterns.

Source
Securiti: Is Securiti a DSPM tool or a privacy tool?

Both, deliberately. It runs data security posture management and privacy operations off one discovery catalogue, which is its main argument against buying two products.

Namespace: What is the difference between Team and Business plans?

Team ($100/mo) includes 100,000 unit minutes and 1,000 Docker builds with email support. Business ($250/mo) includes 250,000 unit minutes, 2,500 Docker builds, and high concurrency with a dedicated Slack channel.

Source
Securiti: What does it cost?

Not published. Pricing is modular and usage based, quoted by data volume and selected modules, and it is also available through the AWS marketplace.

Namespace: Can Namespace support AI coding agents?

Yes, Namespace Devboxes are specifically designed as feature-rich development environments for AI coding agents, with full tooling and performance optimization.

Source
Securiti: How long until it is useful?

Expect months, not weeks. The limiting factor is configuring connectors and getting access approvals to the systems you most want scanned.

Securiti: Does it govern AI use?

Yes, it includes controls over data flowing into models and retrieval pipelines, which is increasingly the reason enterprises shortlist it.

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