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Cybersecurity · head to head

BigID vs Ona (formerly Gitpod)

BigID logo

BigID

Cybersecurity

Data discovery and classification across cloud, on-premise and unstructured stores

From
On request
Free plan
No
Ona (formerly Gitpod) logo

Ona (formerly Gitpod)

Developer Tools

Cloud development environments repositioned as a control plane for software engineering agents

From
Free
Free plan
Yes

The short version

  • Ona (formerly Gitpod) starts at $20/mo; BigID prices on request.
  • Only BigID lists structured and unstructured scanning; only Ona (formerly Gitpod) lists ephemeral environments.
  • Prices and features on this page were last checked on 31 August 2026.

Where they differ

Only the attributes on which BigID and Ona (formerly Gitpod) actually diverge.

Attributes where BigID and Ona (formerly Gitpod) differ
AttributeBigIDOna (formerly Gitpod)
Starting priceOn requestFree
Pricing modelQuotePer month by compute unit
Free tierNoYes
PlatformsWeb, API, Self-hostedWeb, Linux, macOS, Windows, AWS
CategoryCybersecurityDeveloper Tools

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 BigID

  • Structured and unstructured scanning
  • Identity correlation
  • Data security posture management
  • Access intelligence
  • Privacy request support
  • Retention and minimisation
  • AI data controls
  • Policy and remediation workflow

Only in Ona (formerly Gitpod)

  • Ephemeral environments
  • Agent sessions
  • Bring your own cloud
  • Devcontainer standard
  • Compute unit budgeting
  • Enterprise identity

What people use each for

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

BigID

  • A bank that has to prove which of thirty year old file shares contain customer identifiers before a data centre migrationnot Ona (formerly Gitpod)
  • A privacy team that cannot fulfil deletion requests because nobody knows which unstructured stores hold a given customer’s recordsnot Ona (formerly Gitpod)
  • A security team wanting to find sensitive data sitting in publicly readable object storage buckets before an attacker doesnot Ona (formerly Gitpod)
  • A company building retrieval augmented AI that must exclude regulated personal data from the index it feeds to a modelnot Ona (formerly Gitpod)

Ona (formerly Gitpod)

  • Giving a large engineering team identical, disposable environments so onboarding is a link rather than a two day setupnot BigID
  • Running several coding agents in parallel against real databases and services instead of on a laptopnot BigID
  • Keeping source code off contractor and offshore laptops by moving the whole environment into a controlled accountnot BigID
  • Reproducing a hard-to-configure toolchain for a short-lived project without polluting anyone machinenot BigID

Where each one falls short

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

BigID

  • Pricing scales with data sources and volume, so the cost rises exactly as the estate you need to scan grows, and the modules shown in a demo, including AI security posture and headless deployment, are frequently separate licences that appear only in the final quote
  • Scanning large unstructured estates is slow and computationally expensive, so most organisations sample rather than scan everything, which reintroduces uncertainty into the very question they bought the tool to settle
  • Classification accuracy on messy unstructured content requires tuning, and out of the box false positives on things like reference numbers create a large triage backlog that a small governance team cannot clear
  • It discovers and reports but does not remediate, so realising value requires a separate process and often separate tooling to actually delete, restrict or move the data it flags
  • It is built for large enterprises and both the price and the administrative overhead are disproportionate below a few thousand employees, where a lighter DSPM tool covers the security use case for far less

Ona (formerly Gitpod)

  • Acquisition risk has already materialised: the company closed a sale to OpenAI on 10 August 2026 and now sits inside the Codex team, so nothing public guarantees pricing, continuity or neutrality between model vendors beyond honouring existing commitments
  • Two disruptive changes of direction inside a year, from development environments to agent orchestration and then from independence to acquisition, mean the product a browser IDE buyer originally chose no longer exists in that form
  • The Gitpod Classic sunset on 15 October 2025 required manual conversion of configuration, hand-moved secrets, self-rescued workspace data and a brand new account, which is the clearest available precedent for how the vendor handles deprecation
  • Community self-hosting is finished: the AGPL-3.0 repository is deprecated by its own README, and self-hosted now means a vendor-operated install in your AWS or GCP account, with no Azure, no on-premises and no air-gapped path
  • Pricing is difficult to model because it runs on a compute unit currency where subscription credits expire at the end of the month, the mapping from units to actual compute is not published on the pricing page, and Enterprise is quotation only

Pricing, plan by plan

BigID

On request
  • BigID PlatformOn request
    • Priced by number of data sources and data volume
    • Discovery and classification core
    • Optional DSPM, access intelligence and AI security modules licensed separately

Ona (formerly Gitpod)

Free
  • FreeFree
    • Up to 3 parallel environments
    • Machines up to 4 vCPU, 16 GB memory and 80 GB disk
    • Ona Cloud multi-tenant only
  • Core$20/mo
    • From 20 US dollars a month, up to 100 team members
    • Includes 80 to 2,200 recurring compute units a month depending on tier
    • Additional units from 10 US dollars per 40 units
  • EnterpriseOn request
    • Single-tenant deployment in your own AWS or GCP account
    • SAML and OIDC single sign-on
    • Dedicated account management and forward deployed engineers

Which should you pick?

Choose BigID if

  • You need structured and unstructured scanning.
  • You work on Web, API, Self-hosted.
  • You also want identity correlation.

Choose Ona (formerly Gitpod) if

  • You need ephemeral environments.
  • You want to start without paying.
  • You work on Web, Linux, macOS, Windows, AWS.
  • You also want agent sessions.

Questions people ask

Is BigID or Ona (formerly Gitpod) better?
Neither clearly leads. BigID starts at On request and Ona (formerly Gitpod) at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigID or Ona (formerly Gitpod)?
Ona (formerly Gitpod) has a free tier; the other does not. Paid plans start at On request for BigID and Free for Ona (formerly Gitpod).
Does BigID or Ona (formerly Gitpod) run on more platforms?
BigID runs on Web, API, Self-hosted. Ona (formerly Gitpod) runs on Web, Linux, macOS, Windows, AWS.
Can I use Ona (formerly Gitpod) for free?
Yes. Ona (formerly Gitpod) has a free tier, so you can try it without paying. BigID starts at On request.
What is BigID best used for?
BigID is most often used for a bank that has to prove which of thirty year old file shares contain customer identifiers before a data centre migration, a privacy team that cannot fulfil deletion requests because nobody knows which unstructured stores hold a given customer’s records, a security team wanting to find sensitive data sitting in publicly readable object storage buckets before an attacker does, a company building retrieval augmented ai that must exclude regulated personal data from the index it feeds to a model. Of those, a bank that has to prove which of thirty year old file shares contain customer identifiers before a data centre migration and a privacy team that cannot fulfil deletion requests because nobody knows which unstructured stores hold a given customer’s records are not what Ona (formerly Gitpod) is typically brought in for.
What can BigID do that Ona (formerly Gitpod) cannot?
BigID covers Structured and unstructured scanning, Identity correlation, Data security posture management, Access intelligence. Ona (formerly Gitpod) covers Ephemeral environments, Agent sessions, Bring your own cloud, Devcontainer standard.

Answered from the vendors’ own pages

BigID: What does BigID cost?

It is quoted by data source count and volume. Reported contracts run from roughly 15,000 to 175,000 US dollars a year, and add-on modules such as AI security posture are licensed on top.

Ona (formerly Gitpod): Is Gitpod still called Gitpod?

No. It rebranded to Ona in September 2025, and gitpod.io now redirects to ona.com. The company was acquired by OpenAI in a deal that closed on 10 August 2026.

BigID: Does it handle unstructured data?

Yes, and that is its main advantage. It classifies data in files and shares and correlates findings back to individuals, not just to data types.

Ona (formerly Gitpod): Can I still self-host it for free?

No. The AGPL-3.0 self-hosted project is deprecated by its own README. What is offered now is a vendor-operated single-tenant install in your AWS or GCP account on the Enterprise plan.

BigID: Will it delete the data it finds?

Not by itself in most deployments. It identifies and routes findings; deletion and remediation happen through your own processes or connected systems.

Ona (formerly Gitpod): What happened to Gitpod Classic?

Pay-as-you-go Classic was switched off on 15 October 2025. Migration required converting gitpod.yml to devcontainer.json, moving secrets by hand, downloading workspace data before the cutoff and creating a new account.

BigID: Is it a privacy tool or a security tool?

Both are sold from the same discovery core. Buyers increasingly come from security wanting data security posture management rather than from legal wanting privacy.

Ona (formerly Gitpod): What does it cost?

Core starts at 20 US dollars a month and includes a monthly allowance of Ona Compute Units, with more from 10 dollars per 40 units. Subscription credits expire monthly. Enterprise is quoted.

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