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Databases · head to head

ClickHouse vs Immuta

ClickHouse logo

ClickHouse

Databases

Fast open-source column-oriented database for real-time analytics

From
Free
Rated
-
Full reviewWebsite
Immuta logo

Immuta

Databases

Attribute-based access control and masking applied inside Snowflake, Databricks and BigQuery

From
On request
Rated
-
Full reviewWebsite

The short version

  • Only ClickHouse has a free tier, so it costs nothing to try first.
  • Each has a real cost: ClickHouse limited multi-row atomic transactions and expensive UPDATE/DELETE operations unsuitable for transactional systems; Immuta contracts commonly start around one hundred to two hundred thousand US dollars a year for mid-market deployments and exceed five hundred thousand at enterprise scale, which excludes most data teams without a regulatory mandate.
  • They diverge on capability: ClickHouse covers Column-oriented Storage, Immuta covers Attribute-based policy.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which ClickHouse and Immuta actually diverge.

Attributes where ClickHouse and Immuta differ
AttributeClickHouseImmuta
Starting priceFreeOn request
Pricing modelUnknownquote
Free tierYesNo
PlatformsLinux, macOS, Windows (via Docker)Web, API, Cloud
Founded2021Unknown

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

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 ClickHouse

  • Column-oriented Storage
  • Real-time Analytics
  • SQL Support
  • Linear Scalability
  • Data Compression
  • Vectorized Query Execution
  • Approximate Calculations
  • Kafka

Only in Immuta

  • Attribute-based policy
  • Native enforcement
  • Dynamic masking
  • Row-level filtering
  • Purpose-based access
  • Sensitive data tagging
  • Audit logging
  • Multi-platform

What people use each for

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

ClickHouse

  • Business intelligencenot Immuta
  • Data warehousingnot Immuta
  • Real-time analyticsnot Immuta
  • Reportingnot Immuta
  • Machine learningnot Immuta

Immuta

  • A bank whose Snowflake estate has grown to tens of thousands of roles that no one can review before an auditnot ClickHouse
  • A healthcare analytics team that must let researchers query patient data with identifiers masked unless a specific purpose is recordednot ClickHouse
  • A multinational applying different residency and access rules per jurisdiction to the same tables without duplicating datasetsnot ClickHouse
  • An organisation running both Snowflake and Databricks that wants one policy set rather than two divergent implementationsnot ClickHouse

Where each one falls short

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

ClickHouse

  • Limited multi-row atomic transactions and expensive UPDATE/DELETE operations unsuitable for transactional systems
  • Requires upfront schema design discipline with MergeTree engine choices and sort/partition keys
  • Experimental vector search support, not production-ready for vector operations
  • Different query syntax from standard SQL requiring migration planning
  • Limited JOIN capabilities compared to traditional relational databases
  • Migration complexity with 2-4 weeks estimated for data type mapping and query translation

Immuta

  • Contracts commonly start around one hundred to two hundred thousand US dollars a year for mid-market deployments and exceed five hundred thousand at enterprise scale, which excludes most data teams without a regulatory mandate.
  • Policy is only as good as the data classification underneath it, so an organisation with poorly tagged columns will spend months on classification before Immuta enforces anything useful.
  • Native enforcement means capability varies by platform, and a feature available on Snowflake may be absent or behave differently on BigQuery, which undermines the promise of one policy set everywhere.
  • Adding an access governance layer creates a new dependency in the path to data: a misconfigured policy silently returns fewer rows rather than erroring, and analysts can act on incomplete results without noticing.
  • It governs cloud data platforms, so personal data in operational databases, files and SaaS applications sits outside its scope and needs separate controls, meaning Immuta is rarely the whole answer.

Pricing, plan by plan

ClickHouse

Free

No published plan breakdown. See the ClickHouse review.

Immuta

On request
  • Immuta Platform$undefined/year
    • Attribute-based policy authoring
    • Native enforcement in supported data platforms
    • Dynamic masking and row-level security

Which should you pick?

Choose ClickHouse if

  • You need column-oriented storage.
  • You want to start without paying.
  • You work on Linux, macOS, Windows (via Docker).
  • You also want real-time analytics.
ClickHouse review

Choose Immuta if

  • You need attribute-based policy.
  • You work on Web, API, Cloud.
  • You also want native enforcement.
Immuta review

Questions people ask

Is ClickHouse or Immuta better?
Neither clearly leads. ClickHouse starts at Free and Immuta at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClickHouse or Immuta?
ClickHouse has a free tier; the other does not. Paid plans start at Free for ClickHouse and On request for Immuta.
Does ClickHouse or Immuta run on more platforms?
ClickHouse runs on Linux, macOS, Windows (via Docker). Immuta runs on Web, API, Cloud.
Can I use ClickHouse for free?
Yes. ClickHouse has a free tier, so you can try it without paying. Immuta starts at On request.
What is ClickHouse best used for?
ClickHouse is most often used for business intelligence, data warehousing, real-time analytics, reporting. Of those, business intelligence and data warehousing are not what Immuta is typically brought in for.
What can ClickHouse do that Immuta cannot?
ClickHouse covers Column-oriented Storage, Real-time Analytics, SQL Support, Linear Scalability. Immuta covers Attribute-based policy, Native enforcement, Dynamic masking, Row-level filtering.

Answered from the vendors’ own pages

ClickHouse: What is ClickHouse best used for?

ClickHouse is optimized for analytical workloads on large datasets. It excels at fast aggregations and queries, being 10-100x faster than PostgreSQL on large aggregations.

Source
Immuta: Does Immuta sit in the query path?

No. It compiles policies into the data platform's own native controls, so queries run at normal speed through your existing tools.

ClickHouse: Does ClickHouse support transactions?

ClickHouse has limited transaction support and expensive UPDATE/DELETE operations. It is not suitable for transactional workloads requiring strict ACID guarantees.

Source
Immuta: What does it cost?

Not published. Market data suggests roughly 100,000 to 200,000 US dollars a year for mid-market deployments and considerably more at enterprise scale.

ClickHouse: How does ClickHouse compare to PostgreSQL?

ClickHouse is 10-100x faster for analytics but PostgreSQL is better for transactional workloads. Many teams use both: PostgreSQL for writes via MaterializedPostgreSQL replication to ClickHouse for analytics.

Source
Immuta: Is Immuta still independent?

Yes. It remains independently owned, unlike several competitors in data access governance that have been acquired.

Immuta: Does it work across more than one warehouse?

Yes, one policy set can target Snowflake, Databricks, BigQuery and Starburst, though enforcement capability varies by platform.

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