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Cybersecurity · head to head

BigID vs Quantexa

BigID logo

BigID

Cybersecurity

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

From
On request
Rated
-
Full reviewWebsite
Quantexa logo

Quantexa

Cybersecurity

Entity resolution and network analytics for financial crime investigation

From
On request
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Quantexa pricing is never published and lands in the seven figure range annually for a tier one deployment, so it is out of reach for mid-sized institutions no matter how well the analytics would fit.
  • They diverge on capability: BigID covers Structured and unstructured scanning, Quantexa covers Entity resolution.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which BigID and Quantexa actually diverge.

Attributes where BigID and Quantexa differ
AttributeBigIDQuantexa
PlatformsWeb, API, Self-hostedWeb, Linux

Identical on both: starting price (On request), pricing model (quote), free tier (No), user rating (Not yet rated), category (Cybersecurity).

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 Quantexa

  • Entity resolution
  • Network generation
  • Contextual monitoring
  • Investigation workspace
  • Data fusion
  • Deployment on customer cloud

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 Quantexa
  • A privacy team that cannot fulfil deletion requests because nobody knows which unstructured stores hold a given customer’s recordsnot Quantexa
  • A security team wanting to find sensitive data sitting in publicly readable object storage buckets before an attacker doesnot Quantexa
  • A company building retrieval augmented AI that must exclude regulated personal data from the index it feeds to a modelnot Quantexa

Quantexa

  • A bank whose AML alert backlog is dominated by false positives and wants network context to close them fasternot BigID
  • Sanctions investigation where the sanctioned party is not the account holder but a connected director or shareholdernot BigID
  • Merging customer records across retail, commercial and wealth divisions after an acquisition to see total exposurenot BigID
  • A tax or benefits agency looking for organised fraud rings rather than individual claimantsnot 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.

Quantexa

  • Pricing is never published and lands in the seven figure range annually for a tier one deployment, so it is out of reach for mid-sized institutions no matter how well the analytics would fit.
  • Output quality is bounded by input data quality, and organisations without governed customer data spend the first phase of the programme fixing feeds rather than catching criminals.
  • Implementation typically requires a systems integrator and runs into quarters rather than weeks, so the business case has to survive a long period with no operational benefit.
  • The platform augments rather than replaces existing transaction monitoring, so you keep paying for the incumbent system alongside it and total compliance technology spend rises before it falls.
  • Skills are scarce; the platform needs people who understand both Spark scale data engineering and financial crime typologies, and those people are hard to recruit and easy to lose.

Pricing, plan by plan

BigID

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

Quantexa

On request
  • Quantexa Platform$undefined/year
    • Entity resolution and network generation
    • Deployed in customer cloud tenancy
    • Priced by data volume and use case count

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.
BigID review

Choose Quantexa if

  • You need entity resolution.
  • You work on Web, Linux.
  • You also want network generation.
Quantexa review

Questions people ask

Is BigID or Quantexa better?
Neither clearly leads. BigID starts at On request and Quantexa at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigID or Quantexa?
BigID starts at On request and Quantexa at On request.
Does BigID or Quantexa run on more platforms?
BigID runs on Web, API, Self-hosted. Quantexa runs on Web, Linux.
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 Quantexa is typically brought in for.
What can BigID do that Quantexa cannot?
BigID covers Structured and unstructured scanning, Identity correlation, Data security posture management, Access intelligence. Quantexa covers Entity resolution, Network generation, Contextual monitoring, Investigation workspace.

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.

Quantexa: Does Quantexa replace our transaction monitoring system?

No. It usually sits alongside it, adding network context to the alerts that system generates and to investigations.

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.

Quantexa: Where does our data go?

Into your own cloud tenancy in the normal deployment model. Quantexa does not require you to send customer data to a shared multi-tenant service.

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.

Quantexa: How is it priced?

Not publicly. Expect an annual subscription scaled by data volume and number of use cases, plus separate implementation cost.

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.

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