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Cybersecurity · head to head

BigID vs Steampipe

BigID logo

BigID

Cybersecurity

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

From
On request
Free plan
No
Full reviewWebsite
Steampipe logo

Steampipe

Developer Tools

Query cloud APIs, SaaS tools and code with SQL, with no extract or load step

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Only Steampipe has a free tier, so it costs nothing to try first.
  • 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.; Steampipe aGPL-3.0 across all four engines is a procurement blocker at organisations that ban the licence outright, and the network clause reaches any internal portal or service that puts a web interface in front of it.
  • They diverge on capability: BigID covers Structured and unstructured scanning, Steampipe covers SQL over live APIs.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which BigID and Steampipe actually diverge.

Attributes where BigID and Steampipe differ
AttributeBigIDSteampipe
Starting priceOn requestFree
Pricing modelquoteOpen source, with paid hosting through Turbot Pipes
Free tierNoYes
PlatformsWeb, API, Self-hostedmacOS, Linux, Windows, Docker, Web
CategoryCybersecurityDeveloper Tools

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 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 Steampipe

  • SQL over live APIs
  • Wide plugin set
  • Embedded Postgres
  • Compliance benchmarks
  • Joins across providers
  • Hosted option

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

Steampipe

  • Security teams answering posture questions against live cloud accounts rather than a nightly exportnot BigID
  • Compliance evidence gathering where the answer must reflect the account at the moment it is askednot BigID
  • Inventory and drift questions spanning several cloud providers in one querynot BigID
  • Engineers who would rather write SQL than learn each provider command line toolnot 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.

Steampipe

  • AGPL-3.0 across all four engines is a procurement blocker at organisations that ban the licence outright, and the network clause reaches any internal portal or service that puts a web interface in front of it.
  • Dashboards, benchmarks and mods were removed from Steampipe entirely at version 1.0 in October 2024 and now live in a separate product, so pre-2024 documentation and tutorials describe commands that no longer exist.
  • Live querying is bound by cloud provider API rate limits and keeps no persistent store by default, which is why a separate DuckDB-backed product exists for log volumes and why large accounts return slowly.
  • The company is fifteen people and bootstrapped, maintaining four command line tools plus a hosted service plus two further products, and the newer tools have thin community traction relative to that surface area.
  • Hosted tiers include only three users regardless of tier, with additional Enterprise users charged separately, so a team of thirty costs an order of magnitude more than the headline figure before compute and storage are counted.

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

Steampipe

Free
  • Steampipe CLIFree
    • AGPL-3.0
    • All plugins
    • No user or query limits
  • Pipes DeveloperFree
    • One user
    • 400 compute minutes
    • 3GB storage
  • Pipes Team$49/month
    • Three users
    • 2,000 compute minutes
    • 20GB storage
  • Pipes Enterprise$249/month
    • Three users
    • 10,000 compute minutes
    • 100GB storage

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 Steampipe if

  • You need sql over live apis.
  • You want to start without paying.
  • You work on macOS, Linux, Windows, Docker, Web.
  • You also want wide plugin set.
Steampipe review

Questions people ask

Is BigID or Steampipe better?
Neither clearly leads. BigID starts at On request and Steampipe at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, BigID or Steampipe?
Steampipe has a free tier; the other does not. Paid plans start at On request for BigID and Free for Steampipe.
Does BigID or Steampipe run on more platforms?
BigID runs on Web, API, Self-hosted. Steampipe runs on macOS, Linux, Windows, Docker, Web.
Can I use Steampipe for free?
Yes. Steampipe 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 Steampipe is typically brought in for.
What can BigID do that Steampipe cannot?
BigID covers Structured and unstructured scanning, Identity correlation, Data security posture management, Access intelligence. Steampipe covers SQL over live APIs, Wide plugin set, Embedded Postgres, Compliance benchmarks.

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.

Steampipe: When did Steampipe become AGPL?

May 2021, about four months after the project went public. It is a settled licence rather than a recent change, and predates the Business Source Licence wave it is often confused with.

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.

Steampipe: Where did the dashboards and benchmarks go?

Into Powerpipe. They were deprecated in March 2024 and removed from Steampipe at version 1.0 in October 2024, so the check, dashboard, mod and variable commands are gone.

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.

Steampipe: Is it fast on a large cloud estate?

Not always. Queries call provider APIs at request time, so rate limits rather than query planning set the pace, and there is no persistent store by default.

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.

Steampipe: Does the AGPL affect internal use?

Running it internally for your own analysis is fine. Putting a web interface in front of it that other people use is where the network clause becomes a question for your legal team.

Steampipe: Is a bootstrapped vendor a risk?

It cuts both ways. There is no investor pressure toward a licence change or an exit, and there are also fifteen people supporting a large product surface.

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